Data Scientist II

🏢 Summary: Remote Data Scientist V contract role focused on advanced analytics, experimentation, and data-driven decision-making for new product development. The position involves building statistical models, designing A/B tests and KPI frameworks, and partnering with cross-functional teams to influence product strategy. Candidates should have strong expertise in Python, SQL, statistics, and product analytics in fast-paced technology environments. 🗂️ Requirements: Experience supporting 0-to-1 product development with data science, Proficiency in Python, Advanced SQL experience, Strong statistics knowledge, Experience with A/B testing, Experience designing KPI frameworks, Knowledge of operational research techniques, Ability to translate analytical findings into business recommendations, Ability to manage multiple priorities, Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related field, Eligibility to work on direct W2 without sponsorship 📃 Skills: Python, SQL, Statistics, Modeling, Analytics, Forecasting, Optimization, Simulation, Experimentation, Dashboards, Automation, Regression 🏢 Description: itD is seeking a Data Scientist V to drive data-informed decision-making for new product development by delivering advanced analytics, experimentation, and actionable insights across cross-functional teams. The ideal candidate will bring deep expertise in data science, statistical analysis, and product analytics, along with a proven track record of supporting 0-to-1 product development, designing measurement frameworks, and influencing product strategy through data. Duration: 6 Months We provide comprehensive medical benefits, a 401(k) plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities - Analyze large, complex datasets to identify trends, business opportunities, and key drivers that influence product performance. - Design, execute, and evaluate experiments, including A/B tests, KPI frameworks, and measurement strategies for new product initiatives. - Develop reproducible analyses, dashboards, and reporting solutions to enable ongoing product and business performance monitoring. - Build statistical models and operational research solutions to support forecasting, optimization, prioritization, and strategic planning. - Partner with product managers, engineers, and cross-functional stakeholders to translate business questions into scalable analytical solutions. - Present analytical findings and recommendations to technical and non-technical audiences, enabling data-driven product decisions. - Validate data quality, document analytical methodologies, and ensure accuracy and consistency across reporting and insights. Internal Responsibilities - Attend regular internal practice community meetings. - Collaborate with your practice team on industry thought leadership. - Complete client case studies and learning material. - Build out material to contribute to the Digital Transformation practice. - Attend internal networking events. - Work with leadership on career fast-track opportunities. Required Qualifications and Skills - Proven experience using data science to support 0-to-1 product development. - Strong proficiency in Python for data analysis, statistical modeling, and automation. - Advanced experience with SQL for querying, transforming, and analyzing large-scale datasets. - Strong knowledge of statistics, including hypothesis testing, regression analysis, experimental design, and statistical inference. - Experience designing and evaluating A/B tests, KPI frameworks, and measurement methodologies. - Knowledge of operational research techniques, including optimization, simulation, or decision analysis. - Experience translating complex analytical findings into actionable business recommendations. - Ability to manage multiple priorities and deliver high-quality analytical work in a fast-paced environment. Preferred Qualifications and Skills - Experience building or supporting data pipelines or a data engineering background. - Previous experience at a large technology company. - Experience supporting rapid product innovation within consumer technology environments. - Experience partnering closely with product teams on product strategy and experimentation. Education - Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, or a related quantitative field, or equivalent work experience required. Benefits - Comprehensive medical benefits - 401(k) plan - Paid holidays

🏢 Summary: Senior Data Scientist role focused on building and operating real-time, AI-driven decisioning systems that directly impact user experience and conversion rates. The position involves developing and deploying production-grade machine learning models with strict low-latency requirements and contributing to personalization, experimentation, and recommendation systems. It combines hands-on ML engineering with experimentation, causal analysis, and large-scale data processing in a business-facing environment. 🗂️ Requirements: 7+ years commercial experience in Data Science with production ML focus, Strong experience deploying and maintaining production ML models, Experience with real-time systems and low-latency constraints, Proficiency in Python and SQL, Hands-on experience with gradient boosting methods, Experience with recommendation systems and uplift modeling, Strong knowledge of A/B testing and causal inference, Experience building feature engineering pipelines at scale, Experience with Apache Spark or PySpark, Cloud platform experience (AWS preferred), Familiarity with LLMs and GenAI for personalization 📃 Skills: Python, SQL, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, PySpark, Spark, AWS, Databricks, NLP, LLM, GenAI 🏢 Description: We are looking for a Senior Data Scientist to join a Growth Alliance team focused on AI-driven decisioning and user-facing machine learning systems. This role is suited for a technically strong data scientist who is equally comfortable working with business stakeholders and operating production ML systems at scale. About the Project: This is a high-impact role working directly on systems that influence end-user experience and conversion. You will operate in a real-time environment with strict low-latency requirements (<40 ms), contributing to a shift toward AI-driven decisioning aimed at improving product performance and increasing conversion rates. The work spans production ML pipelines, experimentation, and personalization, not just research or experimentation in isolation. Responsibilities: Design, develop, and deploy production machine learning models with real-time constraints; Build and maintain recommendation systems, uplift models, and contextual bandit frameworks; Conduct A/B testing, causal inference analyses, and statistical hypothesis testing; Develop and maintain feature engineering pipelines at scale using PySpark / Apache Spark; Monitor and validate deployed models to ensure performance and reliability; Collaborate closely with business stakeholders to challenge assumptions and define the right problems; Contribute to generative AI and LLM-based personalization initiatives; Work with decisioning platforms, personalization engines, and Martech integrations. Qualifications: 7+ years of commercial experience in Data Science with a strong production ML focus; Proficiency in Python (NumPy, Pandas, Scikit-learn) and SQL; Hands-on experience with gradient boosting methods (XGBoost, LightGBM); Experience with recommendation systems, clustering, NLP, and uplift modeling; Solid background in A/B testing frameworks, causal inference, and statistical modeling; Experience with feature engineering and production ML pipelines at scale; Cloud platform experience, preferably AWS; Familiarity with LLMs, prompt engineering, and GenAI for content personalization; Strong communication skills and ability to work in a highly business-facing environment; Databricks experience is a nice to have. Recruitment Process: Initial interview with our recruitment team; Interview with the hiring manager; Live Coding Assessment; Meeting with the Project Manager. Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.

🏢 Summary: Own and deliver AI & Data Security product capabilities that help organizations securely adopt and scale AI in cloud environments. Define solutions for AI and data discovery, security posture management, and risk mitigation across the AI lifecycle. Collaborate with engineering and security teams to build visibility and control for AI systems in production. 🗂️ Requirements: 3+ years product management experience in security, AI, data, cloud infrastructure, or developer platforms, Strong understanding of cloud environments and application architectures, Knowledge of generative AI systems fundamentals, Understanding of security risks in AI and ML systems in production, Ability to work closely with engineers on technical design and implementation details, Experience using customer feedback to drive product decisions, Eligibility for required US export authorizations 📃 Skills: AI, Security, Cloud, Data, GenerativeAI, MachineLearning, Infrastructure, Architecture, Compliance, Risk, Posture, Discovery 🏢 Description: As a Product Manager II for AI & Data Security at Datadog, you will define and deliver capabilities that help organizations securely adopt and scale AI across their applications and infrastructure. You’ll focus on building products that provide visibility into AI systems and data usage, assess security posture, and enable teams to manage risk across the AI lifecycle. This role sits at the intersection of security, AI, and cloud platforms, and is ideal for a PM who thrives in emerging, ambiguous problem spaces. You will work cross-functionally to shape how customers discover, understand, and secure AI-powered systems in production. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own and drive the roadmap for AI & Data Security capabilities, including AI and data discovery and posture management Define how customers assess and manage the security posture of AI systems, including risks related to configuration, data exposure, and policy compliance Partner with engineering and design to deliver end-to-end product capabilities, from concept through launch and iteration Collaborate with security research teams to identify emerging risks in AI systems and translate them into actionable product features Engage with customers to understand AI adoption patterns and validate solutions that enable secure, scalable operations Define and track success metrics such as product adoption, usage, and impact on customer security workflows Who You Are: 3+ years of product management experience building technical products in areas such as security, AI, data, cloud infrastructure, or developer platforms Strong understanding of modern cloud environments, application architectures, and the fundamentals of generative AI systems Interest in the security challenges introduced by AI and machine learning systems, particularly in production environments Comfortable working closely with engineers and discussing technical design, tradeoffs, and implementation details Experience engaging with customers and using their feedback to inform product decisions and prioritization Ability to navigate ambiguity and translate complex problem spaces into clear product direction and execution Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Generous and competitive benefits package New hire stock equity (RSUs) and employee stock purchase plan Continuous career development and pathing opportunities Employee-focused best in class onboarding Internal mentor and cross-departmental buddy program Friendly and inclusive workplace culture Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. To conform to US export control regulations, candidates should be eligible for any required authorizations from the US government. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$165,000—$215,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

🏢 Summary: Product Manager II role focused on defining and delivering risk-based alerting capabilities within a Cloud SIEM platform to improve signal quality and reduce alert fatigue for security teams. The position drives the vision, design, and lifecycle of scalable detection, enrichment, and prioritization systems using telemetry and contextual risk modeling. You will collaborate cross-functionally to enhance threat detection and incident response workflows at scale. 🗂️ Requirements: 3+ years product management experience in enterprise software for technical users, Experience in security or observability domains, Familiarity with threat detection and incident response workflows, Experience collaborating with engineering and data science teams, Ability to design risk scoring and prioritization models, Data-driven approach to product decisions and metrics, Experience delivering scalable technical systems 📃 Skills: SIEM, Cloud, Telemetry, ThreatDetection, IncidentResponse, RiskScoring, DataAnalysis, SecurityOperations, DetectionEngineering, SaaS 🏢 Description: As a Product Manager II for Risk-Based Alerting within Datadog’s Cloud SIEM, you will define and deliver intelligent alerting systems that help security teams focus on the most critical threats. You’ll work at the intersection of security, data, and user experience to reduce alert noise, improve signal quality, and enable faster, more confident incident response. Partnering closely with customers and internal teams, you will shape how risk is modeled, prioritized, and surfaced across the platform. This role offers the opportunity to influence core security workflows and drive meaningful outcomes for security teams operating at scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Define and drive the product vision for Risk-Based Alerting, focusing on improving signal quality and reducing alert fatigue for security teams Design and evolve risk scoring frameworks using telemetry, user behavior, threat intelligence, and contextual signals Partner with customers and security practitioners to understand triage workflows and translate insights into product improvements Collaborate with engineering, data science, and security teams to build scalable detection pipelines, enrichment systems, and prioritization models Own the end-to-end product lifecycle, from discovery and requirements through launch, iteration, and long-term strategy Define and track success metrics such as alert fidelity, signal-to-noise ratio, MTTD/MTTR, and product adoption Who You Are: 3+ years of product management experience building enterprise software for technical users; experience in security or observability is preferred Familiarity with security operations workflows such as threat detection, incident response, or detection engineering Strong product sense with the ability to balance technical systems thinking and intuitive user experience design Experience working cross-functionally with engineering, data science, and go-to-market teams to deliver impactful products Data-driven and structured in your approach to problem-solving, prioritization, and decision-making Effective communicator, able to translate complex technical concepts into clear value for diverse audiences Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Generous and competitive benefits package New hire stock equity (RSUs) and employee stock purchase plan Continuous career development and pathing opportunities Employee-focused best in class onboarding Internal mentor and cross-departmental buddy program Friendly and inclusive workplace culture Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$165,000—$215,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

🏢 Summary: Engineering Manager role leading a team building LLM-powered natural language interfaces and conversational AI systems for querying telemetry data and configuring platforms. The position focuses on delivering high-quality NLQ, retrieval, and agentic AI capabilities, while driving evaluation, iteration, and operational excellence. It combines hands-on technical leadership with ownership of AI product delivery in a hybrid work environment. 🗂️ Requirements: Experience building and shipping LLM-powered products or conversational AI systems, Strong expertise in AI, Machine Learning, or NLP systems, Hands-on knowledge of LLMs, RAG, semantic search, or agentic systems, Experience designing evaluation pipelines for AI systems, Ability to balance accuracy, latency, cost, and safety in AI systems, Experience leading and mentoring engineers or applied scientists, Ability to collaborate with Product on ambiguous AI problems, Degree in Machine Learning, Computer Science, Engineering, or related field or equivalent experience 📃 Skills: Python, LLM, NLP, RAG, MachineLearning, DeepLearning, SemanticSearch, AgenticSystems, Evaluation 🏢 Description: Datadog's Applied AI group is building the AI capabilities that transform how users interact with our platform. Our Natural Language Query (NLQ) and Command-I (Cmd-I) teams are at the forefront of this transformation, enabling users to query telemetry data, investigate production issues, and configure Datadog through natural language and intelligent conversational agents. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists building natural language interfaces and conversational AI systems. Your teams will work on challenges spanning LLM-powered query translation, context-aware retrieval systems, agentic architectures, and evaluation frameworks. You will guide technical execution, support team growth, and collaborate across engineering, product, and research to deliver AI experiences that fundamentally change how customers use Datadog. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists building NLQ translation systems, conversational agents, or AI-powered interfaces Own the delivery of high-quality natural language capabilities, from semantic understanding and contextual retrieval to query generation and agentic reasoning Build products that create data flywheels: design systems that capture user intent and feedback to continuously improve model quality and train differentiating capabilities Drive evaluation and iteration practices for AI systems, including building offline and online evaluation pipelines to measure quality and detect drift Partner with product managers and cross-functional teams to expand AI capabilities across the Datadog platform Navigate the unique challenges of shipping LLM-powered products: balancing accuracy, latency, cost, and safety considerations Support career growth for engineers through coaching, feedback, and fostering a culture of experimentation, innovation, and learning Drive day-to-day execution and promote high standards for operational excellence, system reliability, and technical quality Participate in hiring and help shape the future team as the organization grows Contribute to cross-team collaboration and knowledge sharing across the broader AI organization Who You Are A technical leader with experience in AI, machine learning, or NLP systems Proven experience building and shipping LLM-powered products, conversational AI, or natural language interfaces A product builder who thinks beyond features, designing systems that generate data, learn from usage, and compound in value over time Experience leading and mentoring engineers; ready to grow into broader leadership responsibilities Strong technical expertise in one or more areas: large language models, retrieval-augmented generation (RAG), semantic search, agentic systems, deep learning, or NLP Comfortable working with Product to break down ambiguous problems, foster an experimental culture and iterate quickly on AI systems where quality is probabilistic Familiarity with evaluation methodologies for AI systems, both offline benchmarks and online metrics A people-focused manager able to develop and support strong engineering talent in a fast-moving domain BS/MS/PhD in Machine Learning, Computer Science, Engineering, or related field, or equivalent professional experience Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one — that's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth New hire stock equity (RSUs) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing An inclusive company culture with the ability to join Community Guilds (Datadog employee resource groups) Free, global Spring Health benefits for employees and dependents age 6+ Competitive global benefits Giving programs Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$187,000—$240,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

🏢 Summary: B2B contract for a Data Scientist working in a hybrid model (3 days onsite in Warsaw) focused on building, implementing, and maintaining statistical and machine learning models supporting actuarial processes. The role involves advanced data analysis, feature engineering, process automation, and close collaboration with actuarial and underwriting teams. 🗂️ Requirements: Very good knowledge of Python for data analysis and modeling, Strong knowledge of machine learning, predictive analytics, and statistical inference, Experience with data processing tools (pandas, SQL), Experience with data visualization tools (matplotlib, seaborn, ggplot2), Experience with code repositories, Strong analytical and problem-solving skills, Ability to work onsite in Warsaw 3 days per week 📃 Skills: Python, MachineLearning, PredictiveAnalytics, Statistics, pandas, SQL, matplotlib, seaborn, ggplot2, Git, SAS, AWS, Azure, Emblem, Radar 🏢 Description: Profil: Data Scientist Miejsce świadczenia usług: model hybrydowy – 3 razy w tygodniu praca z biura (Warszawa) + 2 razy w tygodniu praca zdalna – warunek konieczny. Forma współpracy: B2B. kontrakt Stawka: 150 - 180 zł/h Zakres obowiązków: Projektowanie, wdrażanie oraz utrzymanie modeli statystycznych i modeli uczenia maszynowego wspierających funkcje aktuarialne. Analiza dużych i złożonych zbiorów danych w celu formułowania praktycznych wniosków wspierających procesy decyzyjne. Prowadzenie eksploracyjnej analizy danych (EDA) oraz tworzenie cech (feature engineering) w celu zwiększenia jakości i interpretowalności modeli. Wsparcie automatyzacji i optymalizacji procesów aktuarialnych z wykorzystaniem nowoczesnych narzędzi oraz frameworków data science. Ścisła współpraca z aktuariuszami, underwriterami oraz zespołami likwidacji szkód w celu przekładania potrzeb biznesowych na rozwiązania analityczne. Przygotowywanie prezentacji wyników analiz i rekomendacji w sposób przystępny dla odbiorców technicznych. Wymagania: a. Must-have: Bardzo dobra znajomość języka Python w zakresie analizy danych i modelowania. Solidna wiedza z obszaru uczenia maszynowego, analityki predykcyjnej oraz wnioskowania statystycznego. Doświadczenie w pracy z narzędziami do przetwarzania danych (np. pandas, SQL) oraz wizualizacji danych (np. matplotlib, seaborn, ggplot2). Umiejętność pracy z repozytorium kodu. Silne kompetencje analityczne: rozwinięte umiejętności rozwiązywania problemów i dociekliwość w pracy z danymi. Umiejętność efektywnej komunikacji i współpracy w zespołach interdyscyplinarnych. Dyspozycyjność do pracy w biurze 3 razy w tygodniu. b. Nice-to-have: Znajomość narzędzi pricingowych WTW (Emblem, Radar). Znajomość branży ubezpieczeniowej. Znajomość narzędzi SAS. Znajomość systemów kontroli wersji (Git). Znajomość środowisk chmurowych (AWS, Azure). Benefity: Prywatna opieka medyczna Karta Multisport lub dostęp do kafeterii MyBenefit Ubezpieczenie na życie Co zyskasz dzięki aplikacji na ofertę Antal? Gdy Twoja aplikacja zostanie rozpatrzona pozytywnie (zostaniesz zaproszony/a do procesu), otrzymasz wsparcie Konsultanta/Konsultantki, który/a utrzyma z Tobą stały kontakt (mailowo lub telefonicznie), pomoże Ci przygotować się do rozmowy rekrutacyjnej z przyszłym pracodawcą oraz zatroszczy się o jakość procesu rekrutacyjnego, w którym aktualnie bierzesz udział. Kim jesteśmy? Jesteśmy liderem rekrutacji specjalistów i menedżerów oraz doradztwa w obszarze HR. Marka obecna jest w 35 krajach, w Polsce działa od 1996 roku. Przez ten czas zbudowaliśmy wiele karier kandydatów, dzięki elastycznemu i kompleksowemu podejściu do wszystkich rekrutacji. Antal tworzy ponad 130 profesjonalnych konsultantów ds. rekrutacji, którzy są oni nie tylko skutecznymi rekruterami, ale także wykwalifikowanymi doradcami, specjalizującymi się zarówno w zakresie wybranego sektora, jak i stanowiska.

🏢 Summary: The offer is for a Data Scientist responsible for designing, building, and deploying machine learning and AI solutions that drive marketplace performance at scale. The role covers end-to-end model development, from problem formulation to production, using advanced statistical methods, deep learning, and Generative AI on large-scale data in cloud environments. You will work closely with data engineers and business stakeholders to deliver impactful, production-grade ML systems. 🗂️ Requirements: Experience in data analysis using SQL, Experience building and deploying ML models in production environments, End-to-end experience designing machine learning models, Ability to translate business problems into ML solutions, Strong communication skills with business stakeholders, Experience with ML and AI, especially LLMs, Proficiency in Python, Understanding of statistical and machine learning methods, Practical and theoretical knowledge of Generative AI and Agentic AI, English and Polish proficiency at B2+ level, Degree in Mathematics, Physics, Economics, Computer Science or related field, or equivalent ML/Data Science experience 📃 Skills: Python, SQL, GCP, BigQuery, VertexAI, CloudComposer, Dataflow, Airflow, PySpark, LLM, GenAI, AgenticAI, DeepLearning, Bayesian, Boosting, CausalInference, Optimization, Kubernetes, Docker, Consul, GitHub, GitHubActions, Gemini, GPT 🏢 Description: Data Scientist Location: Warszawa, PL, 00-841 Company: Allegro sp. z o.o. Team: Technology Contract Type: Employee We are looking for a Data Scientist with a strong analytical mindset - someone who enjoys decoding market mechanisms and applying statistical models to solve complex platform puzzles. Our team drives the logic that powers a trustworthy and competitive marketplace. As part of the Tech organization dedicated to delivering the best experiences for our sellers, we specialize in data solutions focused on driving their growth - particularly through optimizing price competitiveness, expanding product selection, and supporting strategic campaigns. Composed of Data Scientists, Data Engineers, and Analysts, we develop statistical models and rules to measure and improve our products and services. We work in close collaboration with developers and product teams across the entire project lifecycle, from ideation to implementation. Our ultimate goal is to create a seamless experience where partners can rely on fair visibility rules, and Customers can trust every product detail they see on the platform. The brain of the entire Allegro. Here, we implement projects based on a practical application of artificial intelligence and Data Science on a scale unprecedented in Poland. In order to effectively implement ML solutions and automate existing processes, we need the support of inquisitive, experienced, and data-driven individuals. The ones willing to be up to date on newest algorithms and advancements in AI, from new deep learning architectures, explainable AI and GenAI but still grounded and aware of statistics and predictive modelling. In Allegro you will work with solutions from prototypes to create stable, high-performance solutions and combine these services with batch and stream processing analyzing real BigData (also in the public cloud). What will your job involve? Co-creating projects on each stage - from concept to productization - to deliver insights and models solving business problems from different areas Using a wide range of model types, including boosting models, Bayesian methods, causal inference, optimization methods, deep learning and Generative AI solutions including LLMs and Agentic AI Working hand-in-hand with our Data Engineers who support the heavy-lifting of data processing on GCP Working not only with tabular data, but also with spatial data, natural language texts, images and time series Taking part in implementations of off-line and on-line models Brainstorm, provide mentorship, share knowledge Cooperation with other teams: business stake-holders, analytics, data engineers Why should you work with us? Data Science plays a key role in the operation of Allegro - we are a data-driven technology company, and through the models and analyses provided you will have a significant impact on one of the largest eCommerce platforms in the world You will have a possibility of developing AI tools from prototypes to large production solutions that will have real impact on our users, merchants and employees. Thanks to the wide range of projects we carry out, you will never run out of interesting challenges Support of experienced Data Scientists - there is always someone to exchange ideas with, because we have the best specialists and experts in their field on board You will have access to huge data sets and the latest data processing technologies You will have the opportunity to learn the tools and technologies in practice: Python (including various ML libraries), GCP environment (BigQuery, VertexAI, Cloud Composer, Dataflow), Airflow, PySpark, Gemini/GPT models You will learn good programming, engineering and code management practices We share our knowledge at industry conferences and trainings, we are an active participant and co-creator of the Data Science / Machine Learning community in Poland and in the world Our offer is addressed to people who: Have experience in data analysis using SQL and building machine learning solutions in production environments, especially with end-to-end experience in designing ML models Want to translate business challenges into ML problems Can clearly communicate with business units - from formulating an analytical problem to a clear and intuitive presentation of results Have experience with ML and AI (especially LLMs) Are highly independent, showing strong work organization and taking full responsibility for their given projects Program in Python and efficiently use basic development tools Understand statistical and machine learning methods Embrace modern tooling, specifically possessing practical and theoretical knowledge of Generative AI and Agentic AI principles (coding tools, prompting, validation). The ideal candidate enthusiastically leverages GenAI coding tools (like Copilot) to boost and automate workflows,  remaining up-to-date and critically engaged with the newest GenAI tooling. Speak English and Polish at a B2+ level or higher Graduated with a degree strongly related to statistical/mathematical modeling, such as Mathematics, Physics, Economics, Computer Science (or similar major) or have job experience in data science / ML positions What's in it for you: Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. Annual bonus based on your annual performance and company results. Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. And that's just the beginning! You can read more about the benefits here . #goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale, which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about! Send us your CV and… see you at Allegro!

🏢 Summary: Staff AI Research Scientist role focused on advancing and deploying large language models and agentic systems for enterprise-scale AI applications. The position involves leading high-impact research across post-training, multi-step reasoning, planning, and alignment, with direct influence on production systems used by major enterprises. This hybrid role offers the opportunity to publish cutting-edge research while shipping innovations into real-world products. 🗂️ Requirements: 7+ years ML research experience, Expertise in large language model pre-training and post-training, Experience training and debugging distributed models at scale, Expert knowledge of SFT, RLHF, RLAIF, DPO, GRPO, Strong proficiency in Python, Strong proficiency in PyTorch or JAX, Experience building scalable training and evaluation pipelines, Proven publication record at top-tier ML/AI conferences, Hands-on experience with agentic systems and multi-step reasoning models, PhD in Computer Science, Machine Learning, NLP or related field (or equivalent research experience) 📃 Skills: Python, PyTorch, JAX, LLMs, SFT, RLHF, RLAIF, DPO, GRPO, NLP, DistributedTraining, DataSynthesis, ModelEvaluation, Alignment, AgenticSystems 🏢 Description: About the role AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers ambitious enterprise AI deployments. As a Staff AI Research Scientist, you'll drive a high-impact research agenda focused on large language models, agentic reasoning, and system-level capabilities that make AI useful at enterprise scale. Your work will advance the field while shipping directly into products used by hundreds of thousands of people. You will work on post-training, planning, multi-step reasoning, and agentic workflows that shape how enterprise AI behaves, performs, and scales. The role is hybrid, based in San Francisco or New York City, reporting to the VP of AI Research. What you'll do - Lead an independent, high-impact research agenda on large language models and agentic systems, owning projects from hypothesis through training, evaluation, and production deployment - Design and execute large-scale post-training experiments using supervised fine-tuning, reinforcement learning from human feedback (RLHF), RLAIF, DPO, and emerging alignment techniques - Improve multi-step reasoning, planning, and tool use in enterprise agentic workflows - Build novel evaluation benchmarks and methodologies for complex enterprise tasks - Develop scalable data synthesis and curation pipelines, including LLM-as-judge frameworks, synthetic data generation, and adversarial dataset construction - Translate research insights into improvements to enterprise-grade LLMs in collaboration with research engineering and product teams - Publish and present original research at top-tier venues such as NeurIPS, ICLR, ICML, and ACL - Mentor researchers and engineers, maintaining high standards for scientific rigor and experimental design What you need - 7+ years of hands-on ML research experience - Deep expertise in large language model pre-training and post-training - Experience training models at scale and debugging distributed jobs - Expert knowledge of SFT, RLHF, RLAIF, DPO, GRPO, and related alignment techniques - Strong command of Python and PyTorch (or JAX) - Experience building scalable training pipelines, evaluation infrastructure, and data synthesis workflows - Publication record at top-tier ML/AI conferences (NeurIPS, ICLR, ICML, ACL, EMNLP or equivalent) - Hands-on experience designing or evaluating agentic systems with multi-step reasoning and tool use - PhD in Computer Science, Machine Learning, NLP, or related field, or equivalent research experience Benefits & perks (US Full-time employees) - Generous PTO and company holidays - Medical, dental, and vision coverage - Paid parental leave (16 weeks) - Fertility and family planning support - Early-detection cancer testing through Galleri - Flexible spending accounts and health savings account with company contribution - Annual wellness and learning stipends - Company-wide and team off-sites - Competitive compensation, stock options, and 401k Compensation Range: $234.3K - $296K

🏢 Summary: Senior Data Scientist / AI Engineer role focused on designing and deploying production-ready AI solutions for the insurance industry. The position involves building Agentic AI systems, LLM and RAG-based applications, and Computer Vision solutions from architecture through production deployment. The offer includes flexible work formats, professional development opportunities, and competitive compensation. 🗂️ Requirements: 5+ years of commercial experience as Data Scientist or AI Engineer, Strong Python development skills, Hands-on experience with Machine Learning, Hands-on experience with Deep Learning, Hands-on experience with Generative AI, Experience with LLMs, Experience with RAG architectures, Experience with AI Agent frameworks, Experience building production AI systems, Solid software engineering background, Experience with data analysis and AI product development, Degree in Computer Science, Data Science, Mathematics, Physics, Engineering or equivalent technical background, Upper-intermediate English level, Ability to design scalable AI solutions 📃 Skills: Python, MachineLearning, DeepLearning, GenerativeAI, LLMs, RAG, ComputerVision, AgenticAI, MultiAgentSystems 🏢 Description: (#5468) N-iX  is looking for an experienced Senior Data Scientist with a strong focus on AI Engineering. The role involves designing and delivering production-ready AI solutions for the insurance industry, with a particular emphasis on Agentic AI, LLMs, RAG pipelines, and Computer Vision. Key Responsibilities: Design and develop autonomous AI agent systems for the insurance domain Build production-ready AI solutions using: Multi-Agent Systems Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Computer Vision Research, evaluate, and implement state-of-the-art AI technologies Develop scalable AI products for international markets Collaborate with a team of Data Scientists and AI Engineers Take AI solutions from architecture and proof of concept through production deployment Participate in building proprietary AI models for the insurance industry Required Skills: 5+ years of commercial experience as a Data Scientist / AI Engineer Strong Python development skills Hands-on experience with: Machine Learning Deep Learning Generative AI LLMs RAG architectures AI Agent frameworks Experience building production AI systems Solid software engineering background Experience with data analysis and AI product development Degree in Computer Science/Data Science/Mathematics/Physics/Engineering or equivalent technical background Upper-intermediate+ English level Strong analytical thinking, proactive mindset Ability to design scalable AI solutions Ability to explain complex technical concepts Independent and structured way of working Team player Nice to Have: Experience within the insurance industry German or Spanish language skills We offer: Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Personalized career growth Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Education reimbursement Memorable anniversary presents Corporate events and team buildings Other location-specific benefits

🏢 Summary: Staff Engineer role focused on designing and building advanced LLM observability features to monitor, evaluate, and debug generative AI systems in production. The position involves leading architecture decisions, prototyping and scaling new capabilities, and improving reliability and performance of LLM-based applications. You will work on scalable backend systems that enable tracing, drift detection, and evaluation of AI workloads. 🗂️ Requirements: BS/MS/PhD in Computer Science, Engineering or related field or equivalent experience, Deep understanding of distributed systems, Experience with scalable backend architectures, Hands-on experience building and shipping LLM or GenAI applications, Understanding of model internals and inference pipelines, Knowledge of LLM evaluation techniques, Experience with prompt engineering, Experience with observability tools or platforms 📃 Skills: LLM, GenerativeAI, DistributedSystems, Backend, Observability, Tracing, DriftDetection, ModelEvaluation, Inference, PromptEngineering, Scalability, Architecture 🏢 Description: The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience Deep understanding of distributed systems and scalable backend architectures Hands-on experience building and shipping LLM-powered or GenAI applications. Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering Ability to thrive in ambiguous, fast-changing spaces and have a product-oriented mindset You’re excited to shape the next generation of AI observability tools from the ground up Communicate clearly, think rigorously, and take pride in clean, maintainable code Experience with observability tools/platforms Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Get to build tools for software engineers, just like yourself. And use the tools we build to accelerate our development. Have a lot of influence on product direction and impact on the business . Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn Competitive global benefits Continuous professional development Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$234,000—$300,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.