Data Scientist V (6223)

🏢 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: Senior Data Scientist SME role supporting federal financial management modernization through advanced data analytics, visualization, and automated reporting solutions in a TS/SCI-cleared environment. The position focuses on transforming complex financial and operational data into actionable insights for audit readiness, financial reporting, and executive decision-making. This is a fully on-site role requiring extensive experience with federal financial systems and business intelligence platforms. 🗂️ Requirements: Active TS/SCI Security Clearance, Bachelor's degree in Accounting, Finance, Business, or related field, 10+ years of experience in federal financial management, accounting, auditing, budgeting, or financial reporting, 5+ years of experience developing dashboards and visualizations using Power BI, Tableau, or similar BI platforms, 5+ years of experience analyzing large financial, budgetary, or operational datasets 📃 Skills: PowerBI, Tableau, SQL, ETL, DAX, ERP, DataModeling, DataVisualization, BusinessIntelligence, DataGovernance 🏢 Description: Clearance: Must have an active TS/SCI Security Clearance. Job Description: In your role as a Data Scientist SME, you will provide expertise supporting financial management modernization efforts through data analytics, visualization, reporting automation, and business intelligence solutions. You will work closely with financial management stakeholders to transform complex financial, budgetary, and operational data into actionable insights that support audit readiness, financial reporting, internal controls, and executive decision-making. Responsibilities: - Design, develop, and maintain enterprise financial dashboards, scorecards, and data visualizations that support financial reporting, audit readiness, and organizational performance management. - Analyze large financial and operational datasets from multiple source systems to identify trends, anomalies, risks, and opportunities for process improvement. - Develop automated reporting solutions that improve the accuracy, consistency, and timeliness of financial information provided to leadership. - Translate complex financial management requirements into intuitive visualizations and reporting products for both technical and non-technical audiences. - Support audit readiness initiatives through data analysis, reconciliation activities, and reporting of key financial metrics. - Develop data models, business rules, and reporting logic to support financial statement preparation, audit support, and management reporting. - Collaborate with functional and technical stakeholders to improve data quality, governance, and reporting capabilities across financial management systems. - Perform financial data validation and reconciliation activities to ensure completeness, accuracy, and reliability of reporting outputs. - Develop standard operating procedures (SOPs), reporting documentation, data dictionaries, and visualization governance artifacts. - Support the development of corrective action plans (CAPs), remediation strategies, and performance monitoring solutions related to audit findings and financial management initiatives. - Research emerging technologies, analytics methodologies, and data visualization best practices to enhance organizational reporting capabilities. - Present analytical findings and recommendations to senior leadership and stakeholders. Required Skills: - Bachelor's degree in Accounting, Finance, Business, or a related field. - 10+ years of experience supporting federal financial management, accounting, auditing, budgeting, or financial reporting initiatives. - 5+ years of experience developing data visualizations, dashboards, and reporting solutions using Power BI, Tableau, or similar business intelligence platforms. - 5+ years of experience analyzing and interpreting large financial, budgetary, or operational datasets. Desired Skills: - Strong understanding of data governance, data quality, and reporting best practices. - CPA, CDFM, CGFM, Microsoft Power BI Data Analyst Associate, Tableau Certified Data Analyst, or similar certification. - Experience developing Power BI semantic models, DAX measures, calculated columns, and advanced visualizations. - Experience integrating data from ERP, accounting, budget, or financial management systems. - Familiarity with OMB Circular A-123, FMFIA, FFMIA, FASAB, and federal financial reporting requirements. - Experience supporting audit remediation, audit liaison activities, CAP development, and NFR remediation. - Experience with SQL, ETL processes, data transformation, and data modeling. - Excellent oral and written communication skills. - Experience briefing senior executives and translating technical findings into business-focused recommendations. Compensation and Benefits: - Salary range: $160,000 to $200,000. - Major medical benefits including dental and vision coverage. - 401(k) contribution plan. - Holiday and personal time off. - Professional development training and certification benefits. - Health and wellness subsidies. - Paid time off for community service.

🏢 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 Data Scientist (Tech Lead) role focused on building and scaling real-time AI-driven decisioning systems to improve product conversion. The position combines hands-on machine learning leadership with technical ownership of production ML pipelines and experimentation strategy. You will drive advanced ML initiatives including recommendation systems, uplift modeling, and LLM-based personalization in low-latency environments. 🗂️ Requirements: 10+ years experience in Data Science with production ML systems, Expert-level Python and SQL, Strong experience with PySpark or Apache Spark, Experience building real-time ML systems with strict latency constraints, Proven experience with gradient boosting and recommendation systems, Strong background in A/B testing and causal inference, Experience building ML pipelines on AWS, Hands-on experience with LLMs including fine-tuning and evaluation, Experience with feature engineering and model monitoring in production 📃 Skills: Python, SQL, PySpark, Spark, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, AWS, Databricks, LLMs, NLP, Clustering, Uplift, Bandits, ABTesting, CausalInference 🏢 Description: We are looking for a Staff Data Scientist to join a Growth Alliance team at the Tech Lead level. This role goes beyond hands-on data science, it requires a candidate who can set technical direction, lead complex ML initiatives, and act as a strategic partner to business stakeholders. You will operate at the intersection of advanced machine learning, real-time systems, and product growth. About the Project: This is a Staff / Tech Lead position within a team driving AI-powered decisioning at scale. You will work on systems with strict real-time constraints (<40 ms latency) that directly impact end-user experience and conversion. The mission is to move the product toward AI-driven decisioning, targeting a measurable improvement in conversion (~5%). You will be expected to challenge assumptions, define the technical roadmap, and ensure that ML systems perform reliably in production. Responsibilities: Lead the design and implementation of production ML systems, including real-time decisioning and personalization engines; Drive adoption of contextual bandits, uplift modeling, and advanced recommendation frameworks; Define experimentation strategy including A/B testing, causal inference, and synthetic controls; Oversee feature engineering at scale and ensure robust model monitoring and validation practices; Act as a technical owner for decisioning platforms and Martech integrations; Collaborate with and influence senior business stakeholders to shape data science strategy; Guide and mentor other data scientists on the team; Lead GenAI and LLM-based initiatives including fine-tuning, evaluation, and content personalization. Qualifications: 10+ years of experience in Data Science, with a strong track record in production ML systems; Expert-level Python (NumPy, Pandas, Scikit-learn) and SQL; Deep experience with PySpark / Apache Spark for large-scale data processing; Mastery of gradient boosting methods (XGBoost, LightGBM), recommendation systems, NLP, clustering, and uplift modeling; Extensive experience with A/B testing, causal inference, statistical modeling, and synthetic controls; Proven ability to build and maintain production ML pipelines on cloud platforms (AWS preferred); Experience with decisioning platforms, personalization engines, and Martech integrations; Hands-on experience with LLMs, prompt engineering, evaluation, and fine-tuning; Strong stakeholder management skills with the ability to challenge assumptions and ask the right questions; 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: The offer is for a remote Data Analyst role within Study Patient Operations, focused on transforming diverse clinical study data into standardized, analysis-ready datasets. The position involves cross-study data harmonization, pattern and anomaly detection, data quality improvement, and building reproducible data pipelines in a regulated environment. The role requires close collaboration with stakeholders to translate ambiguous business questions into structured analytical solutions using modern data tools. 🗂️ Requirements: Proficiency in Python and SQL for data analysis and reproducible workflows, Experience with AWS environments, especially S3 and analytical/query tools, Experience in data standardization and harmonization across heterogeneous datasets, Ability to perform data wrangling, transformation, and validation, Experience in pattern and anomaly detection across multiple datasets, Knowledge of GDPR-compliant data handling and documentation practices, Ability to translate ambiguous business requirements into structured data solutions, Data visualization skills using BI tools, Fluent English (spoken and written) 📃 Skills: Python, SQL, AWS, S3, PowerBI, GDPR, CDISC, SDTM, ADaM, SAS 🏢 Description: Data Analyst within Study Patient Operations About the project We are looking for a Data Analyst in collaboration with a global, science‑driven biopharmaceutical company that uses data and advanced analytics to accelerate the development of innovative therapies. As a Data Analyst in Study Patient Operations, you will transform diverse clinical study data into reliable, analysis‑ready datasets and support cross‑study standardisation and reusability. This role is ideal for someone who thrives in ambiguity, shows strong analytical curiosity, and proactively proposes structured solutions even with incomplete information. Work mode: 100% remote (with one day per month on-site at the client’s office in Warsaw) Tasks Cross‑study data standardisation: Standardise and harmonise data from multiple studies with varying conventions to enable consistent cross‑study analysis. Pattern and anomaly detection: Identify patterns, discrepancies, anomalies, and structural differences across datasets and convert them into actionable mapping rules and validation checks. FAIR data improvement: Strengthen metadata, lineage, definitions, and data quality to enhance data accessibility and reusability, even when documentation is incomplete. Problem framing & stakeholder collaboration: Translate broad or ambiguous business questions into clear data requirements, analytical approaches, and defined pipeline outputs. Data wrangling & transformation: Extract, join, transform, and reconcile datasets using Python, SQL, and AWS‑based tools to support downstream analysis. Compliance, documentation & insight communication: Ensure GDPR‑aligned data handling, maintain audit‑ready documentation, and clearly communicate insights, limitations, and assumptions. Expectations Strong analytical problem‑solving skills in ambiguous contexts and ability to iterate toward clarity. Learning agility , with motivation to quickly understand new domains and clinical data standards. Standardisation mindset , with experience proposing consistent mappings across heterogeneous datasets. Pattern recognition ability across multiple datasets/studies. Proficiency in Python and SQL for analysis, validation, and reproducible workflows. Experience with AWS environments , especially S3 and analytical/querying tools. Data visualisation skills (Power BI or similar). Excellent communication and documentation abilities , especially explaining “what the data means.” Fluent in English (spoken and written) Beneficial Skills Familiarity with clinical trial standards (e.g., CDISC SDTM, ADaM ). Experience with SAS-formatted clinical datasets . Understanding of clinical study processes , privacy/consent principles, and patient data handling. Exposure to machine learning / AI / agentic tools . Interest or experience in LLM-based tooling , especially for metadata, documentation, or analytics workflows. We offer Ongoing support from a dedicated agent , taking care of your project continuity, client contact, necessary formalities, work comfort and development, Consultant Development Program – advice on growth planning based on the latest trends and market needs in IT, including consultations with agents and growth mentors, Access to 7N Learning & Development – a development and educational platform with webinars, a library of articles and industry reports, and regular invitations to one-time and recurring development events – technical, business, and lifestyle, Spectacular integration events , both for you (e.g., annual Kick-Off trip , Christmas parties, or Summer Olympics sports events) and for your loved ones (e.g., family picnics, movie premieres), Professional development not only during the project – you can get involved in knowledge transfer to others within the 7N Services offering directed at 7N clients, Relationships and access to the knowledge of the most experienced IT experts in the market – the average professional tenure of our consultants in Poland is over 10 years, A complete benefits package , including funding for medical care, life insurance, sports cards for you and your loved ones, as well as discounts in stores in Poland and abroad. About 7N Constantly searching for projects, difficult rate negotiations, lack of development support – sounds familiar? At 7N, you gain not only stability of contracts but also the personal involvement of a dedicated agent who ensures your professional comfort and continuous access to development initiatives. Our mission is to provide stable and rewarding collaborations that drive your success as an IT expert and the success of our clients. We build long-lasting relationships based on Scandinavian values and 30 years of experience creating IT solutions for over 200 organizations.

🏢 Summary: Oferta dotyczy pracy na stanowisku Data Scientist przy projektowaniu, wdrażaniu i utrzymaniu rozwiązań machine learning oraz systemów rekomendacyjnych. Rola obejmuje analizę danych, prototypowanie modeli, deployment produkcyjny i współpracę z klientami biznesowymi. Firma oferuje pracę z nowoczesnym stackiem technologicznym, elastyczne warunki oraz możliwość pracy zdalnej. 🗂️ Requirements: Wykształcenie wyższe w obszarze ekonometrii, metod ilościowych, matematyki lub informatyki, Minimum 2 lata doświadczenia jako Data Scientist, Doświadczenie we wdrażaniu komercyjnych projektów analitycznych, Doświadczenie w tworzeniu systemów rekomendacyjnych, Znajomość SQL, Bardzo dobra znajomość Python, Znajomość pandas, Znajomość numpy, Znajomość pyspark, Znajomość polars, Znajomość algorytmów machine learning, Programowanie obiektowe, Znajomość code review, Znajomość CI/CD, Umiejętność pracy z klientem biznesowym 📃 Skills: Python, SQL, Pandas, NumPy, PySpark, Polars, Scikit-learn, SciPy, XGBoost, Spark, Jupyter, Zeppelin, Keras, PyTorch, TensorFlow, Optuna, AWS, Azure, GCP, CI/CD, NLP, LLM, GenAI 🏢 Description: Firma Algomine, należąca do grupy TTPSC, poszukuje Data Scientist Zakres obowiązków: Projektowanie i implementacja rozwiązań wykorzystujących uczenie maszynowe Samodzielna praca na projektach analitycznych i consultingowych Bliska współpraca z klientem, analiza procesów, zbieranie wymagań Prowadzenie analiz eksploracyjnych Prototypowanie rozwiązań analitycznych (uczenie modeli, testowanie podejść) Development i deployment rozwiązań o charakterze produkcyjnym Utrzymywanie i rozwój wdrożonych rozwiązań Prezentacja koncepcji i business-case, omawianie uzyskiwanych wyników Poszukiwane kompetencje: Wykształcenie wyższe o ścisłym profilu: ekonometria, metody ilościowe, matematyka, informatyka Min. 2 lata doświadczenia w roli Data Scientist / we wdrażaniu komercyjnych projektów analitycznych Doświadczenie w tworzeniu i rozwijaniu systemów rekomendacyjnych Wysokie umiejętności przetwarzania danych (SQL, Python: pandas, numpy, pyspark, polars) Dobra znajomość technik i algorytmów machine learning'owych oraz ich implementacji w Python Bardzo dobra znajomość języka Python, w tym programowania obiektowego, optymalizacja kodu Znajomość dobrych praktyk programistycznych (code review, CICD) Dobra komunikacja, umiejętność dialogu z biznesem, prezentacji złożonych koncepcji Mile widziane: Doświadczenie w obszarze doradztwa i consultingu / w pracy dla różnych klientów zewnętrznych, ewentualnie wewnętrznych (np. dział analiz w firmie) / doświadczenie z kilku branż Doświadczenie w projektach end-to-end: od projektu do wdrożenia Doświadczenie we wdrażaniu projektów w obszarach: NLP, LLM, GenAI Znajomość narzędzi służących do przetwarzania dużych zbiorów danych (Apache Spark) Znajomość przynajmniej jednego środowiska chmurowego: AWS, Azure, GCP Stos technologiczny: Open-source: Python, doświadczenie w pracy w notebookach (Jupyter, Zeppelin), Spark (PySpark), Biblioteki: Pandas, Numpy, Scikit-learn, Scipy, Xgboost (mile widziane: Keras, PyTorch, TensorFlow, Optuna) Oferujemy: Nowoczesny stack technologiczny i otwartość na wdrażanie nowych rozwiązań Udział w zróżnicowanych i zaawansowanych technologicznie projektach Data Science Pracę w dedykowanym zespole Data Science Prywatna opieka medyczna i karta sportowa Elastyczny czas pracy i możliwość 100% pracy zdalnej Spotkania integracyjne oraz niezapomniane imprezy firmowe

🏢 Summary: Hybrid Data Analyst role focused on transforming and standardizing clinical study data into analysis-ready datasets, enabling cross-study consistency and reusability. The position involves data wrangling, anomaly detection, FAIR data improvements, and building reproducible workflows using Python, SQL, and AWS tools. The role requires close collaboration with stakeholders to translate ambiguous business questions into structured analytical outputs within a GDPR-compliant environment. 🗂️ Requirements: Proficiency in Python for data analysis and transformation, Proficiency in SQL for querying and validation, Experience with AWS environments including S3, Experience standardizing and harmonizing heterogeneous datasets, Ability to detect patterns, anomalies, and structural differences across datasets, Experience building reproducible data workflows, Experience with data visualization tools, Knowledge of GDPR-compliant data handling, Fluent English (spoken and written) 📃 Skills: Python, SQL, AWS, S3, PowerBI, GDPR, CDISC, SDTM, ADaM, SAS, MachineLearning, AI, LLM 🏢 Description: Data Analyst within Study Patient Operations About the project We are looking for a Data Analyst in collaboration with a global, science‑driven biopharmaceutical company that uses data and advanced analytics to accelerate the development of innovative therapies. As a Data Analyst in Study Patient Operations, you will transform diverse clinical study data into reliable, analysis‑ready datasets and support cross‑study standardisation and reusability. This role is ideal for someone who thrives in ambiguity, shows strong analytical curiosity, and proactively proposes structured solutions even with incomplete information. Work mode: hybrid — based in Warsaw, with one day per week on-site at the client’s office . Tasks Cross‑study data standardisation: Standardise and harmonise data from multiple studies with varying conventions to enable consistent cross‑study analysis. Pattern and anomaly detection: Identify patterns, discrepancies, anomalies, and structural differences across datasets and convert them into actionable mapping rules and validation checks. FAIR data improvement: Strengthen metadata, lineage, definitions, and data quality to enhance data accessibility and reusability, even when documentation is incomplete. Problem framing & stakeholder collaboration: Translate broad or ambiguous business questions into clear data requirements, analytical approaches, and defined pipeline outputs. Data wrangling & transformation: Extract, join, transform, and reconcile datasets using Python, SQL, and AWS‑based tools to support downstream analysis. Compliance, documentation & insight communication: Ensure GDPR‑aligned data handling, maintain audit‑ready documentation, and clearly communicate insights, limitations, and assumptions. Expectations Strong analytical problem‑solving skills in ambiguous contexts and ability to iterate toward clarity. Learning agility , with motivation to quickly understand new domains and clinical data standards. Standardisation mindset , with experience proposing consistent mappings across heterogeneous datasets. Pattern recognition ability across multiple datasets/studies. Proficiency in Python and SQL for analysis, validation, and reproducible workflows. Experience with AWS environments , especially S3 and analytical/querying tools. Data visualisation skills (Power BI or similar). Excellent communication and documentation abilities , especially explaining “what the data means.” Fluent in English (spoken and written) Beneficial Skills Familiarity with clinical trial standards (e.g., CDISC SDTM, ADaM ). Experience with SAS-formatted clinical datasets . Understanding of clinical study processes , privacy/consent principles, and patient data handling. Exposure to machine learning / AI / agentic tools . Interest or experience in LLM-based tooling , especially for metadata, documentation, or analytics workflows. We offer Ongoing support from a dedicated agent , taking care of your project continuity, client contact, necessary formalities, work comfort and development, Consultant Development Program – advice on growth planning based on the latest trends and market needs in IT, including consultations with agents and growth mentors, Access to 7N Learning & Development – a development and educational platform with webinars, a library of articles and industry reports, and regular invitations to one-time and recurring development events – technical, business, and lifestyle, Spectacular integration events , both for you (e.g., annual Kick-Off trip , Christmas parties, or Summer Olympics sports events) and for your loved ones (e.g., family picnics, movie premieres), Professional development not only during the project – you can get involved in knowledge transfer to others within the 7N Services offering directed at 7N clients, Relationships and access to the knowledge of the most experienced IT experts in the market – the average professional tenure of our consultants in Poland is over 10 years, A complete benefits package , including funding for medical care, life insurance, sports cards for you and your loved ones, as well as discounts in stores in Poland and abroad. About 7N Constantly searching for projects, difficult rate negotiations, lack of development support – sounds familiar? At 7N, you gain not only stability of contracts but also the personal involvement of a dedicated agent who ensures your professional comfort and continuous access to development initiatives. Our mission is to provide stable and rewarding collaborations that drive your success as an IT expert and the success of our clients. We build long-lasting relationships based on Scandinavian values and 30 years of experience creating IT solutions for over 200 organizations.

🏢 Summary: Fully remote Data Scientist II role focused on applied research and production deployment of Large Language Models to enhance Conversational AI systems. The position involves designing prompting and orchestration strategies, optimizing RAG pipelines, and building experimentation frameworks for non-deterministic model evaluation. You will collaborate cross-functionally to translate model insights into product and business impact while advancing Generative AI capabilities. 🗂️ Requirements: Master’s degree in Computer Science, Artificial Intelligence, Computational Linguistics, Operations Research, Industrial Engineering, or related field, 2+ years of experience as a Data Scientist, 2+ years of Python programming experience, 2+ years of experience designing LLM interaction flows, evaluation frameworks, or advanced prompting strategies, 2+ years of experience deploying GenAI/LLM solutions into production with engineering teams, 1+ year of experience with Generative AI, LLMs, RAG, and Semantic Search/Vector Databases, 1+ year of experience implementing advanced prompting techniques (Chain-of-Thought, Few-Shot), 1+ year of experience with dialogue systems and context management, Hands-on experience with LLM orchestration frameworks (LangChain or LangGraph), Experience with Transformer architectures (Attention, tokenization, context windows), Experience with SQL 📃 Skills: Python, LLM, GenerativeAI, RAG, SemanticSearch, VectorDatabases, LangChain, LangGraph, Transformers, SQL, Chain-of-Thought, Few-Shot, Tokenization, Embeddings, Attention 🏢 Description: Position Overview At LivePerson, the Data Scientist II helps advance Conversational AI by applying research and experimentation with Large Language Models (LLMs) to real-world customer interactions. This role designs and executes applied research initiatives, develops effective prompting and orchestration strategies using deep knowledge of transformer architectures, and optimizes modern LLM inference and retrieval pipelines. The scientist analyzes large-scale conversational datasets to improve Retrieval-Augmented Generation (RAG) systems and builds robust experimentation frameworks for evaluating non-deterministic model outputs. Working closely with other scientists and cross-functional teams, this role translates insights on model behavior into recommendations that inform product and business strategy while staying at the forefront of Generative AI advancements. Key Responsibilities & Impact - Propose, plan, and execute applied research initiatives that will make a real-world impact on Conversational AI using Large Language Models (LLMs) within a commercial setting. - Use expert knowledge of Transformer architecture mechanics (Attention, Tokenization, Embeddings) to consistently find effective, efficient, stable, explainable prompting and orchestration approaches. - Utilize modern LLM inference and retrieval pipelines. - Analyze large scale conversational datasets for RAG optimization. - Bring research-inspired prompt strategies to life within production systems. - Create durable, flexible scientific evaluation and experimentation capabilities for non-deterministic model outputs. - Present findings on model behavior and context efficacy to inform and guide business and product strategy. - Work closely with other scientists. - Stay current with the rapidly evolving state of Generative AI. Required Skills & Qualifications - Master’s degree in Computer Science, Artificial Intelligence, Computational Linguistics, Operations Research, Industrial Engineering, or a directly related field plus two (2) years of experience as a data scientist. - Two (2) years of experience in: - Programming experience in Python - Developing and designing Large Language Model (LLM) interaction flows, evaluation frameworks, or advanced prompting strategies - Partnering with engineering teams to deploy GenAI/LLM solutions into production - One (1) year of experience in: - Generative AI, including Large Language Models, Prompt Engineering, Retrieval Augmented Generation (RAG), and Semantic Search/Vector Databases - Researching and implementing advanced prompting techniques, such as Chain-of-Thought or Few-Shot prompting - Dialogue systems and context management - LLM Orchestration Frameworks, such as LangChain / LangGraph - Transformer architectures, including Attention mechanisms, Context Windows, and Tokenization constraints - SQL The salary range for this role will be between $120,000 to $145,000 USD. Final compensation will be determined by location, skills, experience, education, and/or professional certifications. Our Benefits & Perks Health & Wellbeing - Medical, Dental, and Vision Insurance - Wellness resources and Employee Assistance Program (EAP) Financial Security & Growth - 401(k) Retirement Plan with 4% employer match - HSA & FSA plans - Employee Stock Purchase Program (ESPP) - Basic and supplemental life insurance, AD&D, disability insurance, legal plan, identity theft protection, and critical illness supplemental insurance - Access to internal professional development resources Time Away & Family Support - Flexible Paid Time Off (PTO) - Paid public holidays - Generous parental leave policy Workplace Flexibility - Fully remote role with optional WeWork space access

🏢 Summary: Senior Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!