Data Scientist

🏢 Summary: Role for a Data Architect responsible for designing and optimizing logical data models and ETL/ELT processes in a Snowflake environment to support decision-making. The position focuses on building efficient, scalable data architectures and bridging business requirements with technical solutions. The offer emphasizes ownership of data modeling, performance optimization, and modern data warehouse development. 🗂️ Requirements: Proven experience in data modeling design and implementation, Experience in designing and optimizing ETL/ELT processes, Experience with Snowflake and large datasets, Knowledge of data warehouse architectures, Experience with relational database design, Ability to translate business requirements into technical data solutions, Experience with data modeling tools, English level B2 or higher, Polish language proficiency 📃 Skills: Snowflake, SQL, Python, Jinja, Snowpark, DBT, Dagster, Airbyte, GitLab, ETL, ELT, DataModeling, DataWarehousing, Databases 🏢 Description: Czy to Ciebie szukamy? Szukamy eksperta, który dołączy do Data Architects Team i weźmie odpowiedzialność za projektowanie logicznego modelu danych wspierającego procesy decyzyjne naszej organizacji. Twoim nadrzędnym celem będzie optymalizacja procesów ETL/ELT, co bezpośrednio przełoży się na maksymalną wydajność i spójność naszego ekosystemu analitycznego. Wykorzystując środowisko Snowflake i język SQL, staniesz się pomostem między światem biznesu a technologią, kształtując nowoczesną architekturę danych. Dołącz do nas, jeśli cenisz niezależność i chcesz mieć realny wpływ na innowacyjne rozwiązania w zarządzaniu danymi. Twoja rola w naszym zespole: analiza wymagań biznesowych i ich transformacja na techniczne rozwiązania rozwijające nasz model danych, zarządzanie logicznymi modelami odzwierciedlającymi strukturę informacji i realnie wspierającymi działania biznesowe, projektowanie oraz ciągła optymalizacja procesów ETL / ELT gwarantująca ich najwyższą wydajność i niezawodność, modelowanie zdarzeń biznesowych i tworzenie struktur w bazach relacyjnych pod kątem przepływu danych, identyfikowanie i wdrażanie nowych rozwiązań technologicznych usprawniających obszar zarządzania informacją, tworzenie i aktualizacja przejrzystej dokumentacji architektonicznej celem zapewnienia zgodności i łatwości utrzymania systemów. Co musisz umieć: Doświadczenie: doświadczenie w projektowaniu i wdrażaniu modeli danych, doświadczenie w projektowaniu przetwarzań danych ETL / ELT oraz struktur bazodanowych, doświadczenie w przygotowywaniu projektów architektonicznych z zakresu modelowania danych, doświadczenie w pracy ze środowiskiem Snowflake i dużymi zbiorami danych, znajomość architektur hurtowni danych oraz narzędzi do modelowania danych. Języki: polski, angielski na poziomie co najmniej B2. Znajomość narzędzi: środowisko Snowflake (mile widziany badge Snowflake Badge 1-6 i Snowflake Certificate Pro), SQL, Python, Jinja, Snowpark, narzędzia: DBT, Dagster, Airbyte, repozytorium GitLab lub podobne. Umiejętności miękkie: umiejętność przejrzystej i efektywnej komunikacji z inżynierami i interesariuszami biznesowymi, zdolność tłumaczenia złożonych zagadnień na prosty i zrozumiały język techniczny oraz biznesowy, samodzielność, kreatywność oraz nastawienie na współpracę i wspólne rozwiązywanie problemów, elastyczność i interdyscyplinarność. Co dostajesz w pakiecie: prywatna opieka LuxMed, bezpłatne badania profilaktyczne oraz masaże odciążające kręgosłup, budżet na doposażenie stanowiska pracy zdalnej oraz vouchery podarunkowe, śniadania w formie bufetu przygotowywane na miejscu, wyjazdy integracyjne i rodzinne do prywatnego ośrodka nad jeziorem, dofinansowanie karty Multisport. Kim jesteśmy i dlaczego warto nas poznać: Trans.eu W sercu cyfrowej rewolucji w transporcie. Od 2004 roku tworzymy jedną z największych platform logistycznych w Europie , łącząc przewoźników, spedytorów i załadowców w jednym miejscu. Automatyzujemy procesy, podnosimy bezpieczeństwo transakcji i sprawiamy, że transport jest bardziej efektywny . Jesteśmy międzynarodową firmą technologiczną działającą w 63 krajach, i dopiero się rozkręcamy. Tworzymy nowoczesne cyfrowe rozwiązania dla transportu, spedycji i logistyki, napędzane wiedzą najlepszych programistów, specjalistów customer experience, inżynierów machine learning i ekspertów AI . Jeśli chcesz kształtować przyszłość technologii w transporcie - to miejsce dla Ciebie! W Trans.eu wierzymy w Smart & Fair Logistics - bardziej wydajną i transparentną branżę. Dlatego powiększyliśmy naszą grupę kapitałową, budując sieć wyspecjalizowanych firm, które pomagają nam realizować tę misję.

🏢 Summary: Mid/Senior Data Scientist role focused on developing and deploying machine learning models and geospatial analytics solutions within SaaS products and R&D projects. The position involves working with large-scale spatial data, building predictive models, and enhancing a Location Intelligence platform. The role combines advanced analytics, Big Data processing, and practical use of LLMs to deliver business insights. 🗂️ Requirements: Minimum 3 years of experience in Data Science, Experience in building predictive machine learning models, Practical experience with SQL databases, Proficiency in Python programming, Experience with geospatial functions in SQL or PySpark, Experience with geospatial libraries, Knowledge of statistics and econometrics, Experience processing large datasets, Experience with Big Data tools, Ability to use LLMs in analytical workflows, English proficiency 📃 Skills: Python, SQL, PySpark, Databricks, AWS, S3, GeoPandas, Shapely, Snowflake, LLM, Claude, Cortex, MachineLearning, Statistics, Econometrics, BigData 🏢 Description: Kilka słów o nas: Jesteśmy firmą technologiczną działającą w obszarze geoanalityki i machine learning . Nasze analizy i technologia pomagają podejmować strategiczne decyzje biznesowe największym firmom z branży retail, mediowej oraz FMCG. Wykorzystując dane przestrzenne pomagamy naszym klientom optymalizować sieć sprzedaży oraz określać najlepsze lokalizacje do jej rozwoju. Jak to robimy? Codziennie miliony użytkowników urządzeń mobilnych raportuje nam o swojej lokalizacji, a dzięki dodaniu kontekstu geoprzestrzennego i socjodemograficznego z zewnętrznych baz danych, oraz zaawansowanym modelom predykcyjnym, które rozwijamy, jesteśmy w stanie w kompleksowy sposób poznać preferencje i ruch klientów w świecie offline. Z naszego rozwiązania już dziś korzystają najwięksi gracze na rynku, nie osiadamy jednak na laurach i wciąż rozwijamy dataplace.ai oraz naszą technologię. Kogo szukamy? Aktualnie szukamy nowego talentu, który dołączy do naszego zespołu Data Science . Poszukujemy osoby, która potrafi pracować na dużych zbiorach danych, rozumie działanie modeli uczenia maszynowego i nie boi się danych przestrzennych. Co będzie należało do Twoich zadań w dataplace.ai? Pracując na stanowisku mid/senior data scientist będziesz zajmował/a się pracą na danych w ramach rozwijanych przez nas produktów SAAS (np. aplikacja location intelligence - placeme), przy projektach klienckich oraz w ramach dużego projektu B+R, który realizujemy. W szczególności do Twoich obowiązków będzie należało: Praca z modelami nauczania maszynowego – tworzenie, wdrażanie i utrzymywanie modeli nauczania maszynowego przy użyciu algorytmów regresji liniowej i logistycznej, klasyfikacji, drzew decyzyjnych itp.; Analityka geoprzestrzenna – praca na danych opartych na lokalizacji w celu określenia zależności i identyfikacji insight’ów, które wzbogacą procesy decyzyjne klientów; Programowanie obiektowe w Python – rozwijanie i utrzymywanie naszej platformy Location Intelligence; Praca z Big Data – przetwarzanie dużych ilości danych, wykorzystując technologię i narzędzia, takie jak PySpark, SQL, Databricks, AWS S3; Wykorzystywanie LLM (Claude, Snowflake Cortex) do automatyzacji analiz i generowania insightów; Udział w pracach B+R – uczestnictwo w pracach badawczych nad rozwojem naszej technologii przetwarzania danych przestrzennych; Opracowywanie i utrzymywanie dokumentacji projektowej; Wsparcie techniczne dla młodszych stażem członków zespołu Data Science. Poza pracą na danych, do Twoich zadań należało będzie też: Ścisła współpraca z zespołem Sales - proponowanie rozwiązań analitycznych, przedstawianie rekomendacji, szacowanie zasobochłonności prac; Przygotowywanie i prezentowanie wyników przeprowadzonych analiz, również poprzez ich wizualizację; Sporadyczne prowadzenie warsztatów dla nowych i obecnych klientów Czego oczekujemy na tym stanowisku? Doświadczenia (przynajmniej 3 lata) w data science, obejmującego rozwiązywanie problemów biznesowych w oparciu o eksplorację danych i machine learning; Znajomości metod tworzenia modeli predykcyjnych; Praktycznej wiedzy i umiejętności pracy na bazach danych z wykorzystaniem SQL; Wiedzy i doświadczenia w programowaniu w Python; Doświadczenia z funkcjami geoprzestrzennymi (SQL, PySpark) oraz bibliotekami do pracy z danymi przestrzennymi (GeoPandas, Shapely); Wiedzy z zakresu ekonometrii i statystyki Umiejętności współpracy z klientami, aby zrozumieć ich potrzeby i korelacje biznesowe analizowanych danych; Umiejętności dobierania metod i narzędzi do analizy, wizualizacji i prezentacji danych; Umiejętności biegłego wyciągania wniosków na podstawie liczb i komunikacji ich do biznesu; Samodzielności, zaangażowania i poczucia odpowiedzialności za tworzone analizy; Znajomości języka angielskiego pozwalającej na swobodną komunikację (w mowie i piśmie). Twoim dodatkowym atutem będzie: Praktyczne wykorzystywanie LLM w codziennej pracy; Doświadczenie pracy z AWS; Umiejętność pracy na Snowflake; Znajomości języka PySpark w kontekście pracy na dużych zbiorach danych (na platformie Databricks); Co oferujemy w zamian? Wynagrodzenie adekwatne do posiadanego doświadczenia – aplikując, podziel się z nami swoimi oczekiwaniami . Preferujemy umowę UoP lub UZ Pracę z ludźmi, którzy lubią to, co robią i siebie nawzajem :) Możliwość pracy w pełni zdalnej – pracujemy z Portugalii, Wiednia czy Giżycka, ale jeśli wolisz przychodzić do biura, zapraszamy do naszej warszawskiej lokalizacji; Elastyczne godziny pracy – łapiemy się na statusy, określamy cele i terminy, ale to Ty decydujesz, kiedy zaczynasz i kończysz pracę (wspólnie ustalamy zasady); Urlop no limit – bierzesz tyle urlopu, ile chcesz, ważne żebyśmy wspólnie dowozili zadania, na które się umówimy; Pracę przy projektach z zakresu ML i Data Science dla największych firm w Polsce; Pracę nad innowacyjnym produktem location intelligence, w którego rozwoju będziesz miał/a swój realny udział; Indywidualnie dopasowany pakiet benefitów; powiedz nam czego oczekujesz, a my powiemy Ci co możemy Ci zaoferować; Możliwość stałego podnoszenia kwalifikacji - Ty wybierasz, jakie szkolenie jest Ci najbardziej potrzebne. Jeśli fascynują Cię dane przestrzenne i chcesz pracować z nowoczesnymi technologiami, dołącz do naszego zespołu i pomóż nam rozwijać innowacyjne rozwiązania w zakresie danych geoprzestrzennych!

🏢 Summary: The offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.

🏢 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: Opportunity for a Data Scientist to build and optimize a near real-time AI-driven intelligence platform in a highly regulated environment. The role focuses on developing scalable data pipelines, integrating and monitoring Large Language Models, and transforming unstructured data into actionable insights. You will drive automation and model performance within a cloud-based data ecosystem. 🗂️ Requirements: Expert-level Python for data processing and AI orchestration, Experience building scalable ETL/ELT pipelines, Hands-on experience with LLM frameworks and prompt engineering, Experience ingesting data from APIs, RSS feeds, and web scraping, Experience managing raw data structures in cloud data platforms, Experience deploying AI models to production environments, Knowledge of model monitoring and hallucination detection, Proficiency with version control using Git 📃 Skills: Python, ETL, ELT, LLM, NLP, APIs, RSS, WebScraping, Git, Cloud, DevOps, PromptEngineering 🏢 Description: Billennium is a global technology company with over 20 years of experience, committed to innovation and empowering businesses. As an employer, we offer a supportive, growth-focused environment where collaboration and creativity thrive. Join us to shape the future of technology together! We are looking for a skilled Data Scientist to join an innovative AI initiative for a client in a highly regulated industry. The project focuses on transforming a periodic monitoring tool into a near real-time, daily intelligence platform Key Responsibilities: Ingestion Pipeline Development: Design, build, and maintain robust data pipelines using Python and cloud-based data platforms to ingest data from diverse sources such as RSS feeds, APIs, and web scraping. Data Platform Architecture: Manage raw data structures and ensure seamless data flow between ingestion pipelines and downstream applications. LLM Integration & Optimization: Implement and refine Large Language Models (LLMs) to categorize, summarize, and extract advanced insights (“Reasoning Modelling”) from unstructured data. LLM Ops: Establish monitoring frameworks for model performance, including hallucination detection, and implement continuous improvement loops based on expert feedback. Scalability & Automation: Support the transition to a fully automated 24-hour processing cycle within the data platform ecosystem. Technical Skills & Qualifications: Programming: Expert-level Python, particularly in data processing and AI orchestration. Data Engineering: Strong experience building scalable ETL/ELT pipelines in modern data platforms. AI / NLP: Hands-on experience with LLM frameworks and prompt engineering. Web Data Ingestion: Proficiency in handling RSS feeds, APIs, and both structured and unstructured web data. DevOps / LLM Ops: Familiarity with version control (Git) and deploying AI models into production environments. Perks and benefits: Comprehensive benefits - enjoy Udemy for Business, private medical care, Multisport card, veterinary package, language lessons, and shopping vouchers. Flexibility - adaptable working hours and remote/hybrid work options to suit your lifestyle & location. Career growth - access opportunities for professional development and learning, including perks related to our official partnerships with global IT giants: Microsoft, AWS, Snowflake, Salesforce & more. Global collaboration - work with a diverse, international team. Innovative environment - be part of a forward-thinking and growth-oriented workplace. Engaging community – Work with passionate professionals and participate in team-building events, hackathons, and CSR initiatives to make an impact beyond work. Team-building events including our company tradition (annual company event in Mazury ). A pleasant surprise to start your journey with us in the form of a welcome pack. Recruitment process: HR call Technical Interview Interview with the dedicated Client Final decision/ Feedback Sounds interesting? Click "Apply" and have a chance to hear more!

🏢 Summary: Role focused on designing, building, and deploying AI/ML solutions end-to-end, from data exploration and experimentation to production deployment and MLOps. The position combines Data Science, ML Engineering, and collaboration with business stakeholders to translate data into actionable solutions. You will develop and maintain ML pipelines, monitor models, and contribute to AI standards within the organization. 🗂️ Requirements: Minimum 1.5 years of experience in Data Science, ML Engineering or MLOps, Proficiency in Python, Experience with ML/DL libraries (scikit-learn, pandas, numpy, PyTorch or TensorFlow), Knowledge of SQL, Experience working with structured and unstructured data, Experience building and deploying ML/AI models, Knowledge of Docker, Knowledge of Git or GitHub, Understanding of CI/CD basics, Experience with MLflow, DVC or Weights & Biases, Knowledge of statistics, model validation and A/B testing, English level B2 or higher 📃 Skills: Python, SQL, scikit-learn, pandas, numpy, PyTorch, TensorFlow, Docker, Git, GitHub, CI/CD, MLflow, DVC, Weights&Biases, MachineLearning, MLOps, Statistics, ABtesting 🏢 Description: Chcesz tworzyć rozwiązania AI, które mają realny wpływ na biznes? Szukamy osoby, która swobodnie porusza się między analizą danych, Machine Learningiem i MLOps, a jednocześnie potrafi rozmawiać z biznesem i przekładać dane na konkretne decyzje oraz wdrożenia. Dołączysz do zespołu rozwijającego nowoczesne rozwiązania AI — od eksploracji danych i eksperymentów, po wdrożenia modeli i rozwój standardów AI w organizacji. Wymagania Min. 1,5 roku doświadczenia w obszarze Data Science, ML Engineering lub MLOps Bardzo dobra znajomość Python oraz bibliotek ML/DL (scikit-learn, pandas, numpy, PyTorch lub TensorFlow) Znajomość SQL oraz pracy z danymi strukturalnymi i niestrukturalnymi Doświadczenie w budowie i wdrażaniu modeli ML/AI Znajomość Docker, Git/GitHub oraz podstaw CI/CD Doświadczenie z narzędziami MLflow, DVC lub Weights & Biases Wiedza z zakresu statystyki, walidacji modeli i testów A/B Umiejętność współpracy z biznesem i prezentowania wyników analiz Analityczne myślenie, dobra organizacja pracy i nastawienie na rezultat Język angielski min. B2 Mile widziane Wykształcenie kierunkowe (informatyka, matematyka, data science lub pokrewne) Doświadczenie w pracy z politykami bezpieczeństwa danych i etyką AI Zadania na stanowisku Analiza danych i identyfikacja obszarów do wykorzystania AI oraz ML Projektowanie, trenowanie i wdrażanie modeli Machine Learning Prowadzenie eksperymentów i monitorowanie jakości modeli po wdrożeniu Rozwój pipeline’ów CI/CD oraz konteneryzacja środowisk ML z użyciem Docker Wersjonowanie modeli, danych i kodu oraz dokumentowanie prac projektowych Współpraca z zespołami Data Engineering, Backend i DevOps Prezentowanie wyników analiz oraz rekomendacji dla biznesu Udział w rozwoju standardów i rozwiązań AI w organizacji Co oferujemy Udział w nowoczesnych projektach AI i Data Science Pracę z nowoczesnym stackiem technologicznym Realny wpływ na rozwój rozwiązań analitycznych w organizacji Wynagrodzenia złożone z podstawy i premii - regulaminowej rozliczanej kwartalnie (budżet premii 10% wynagrodzenia zasadniczego kwartalnego) Możliwość doskonalenia zawodowego - finansowane przez firmę szkolenia i podnoszenie kwalifikacji Pakiet benefitów - prywatna opieka medyczna, ubezpieczenia grupowe, możliwość skorzystania z pakietu sportowego (karta Multisport) Dostęp do platformy e-learningowej z bogatą bazą kursów Imprezy integracyjne

🏢 Summary: Design and build a modern data platform from scratch for an insurance client, covering architecture, data ingestion, modelling, and production operations. The role focuses on establishing a governed, scalable Snowflake-based environment to enable reliable reporting and AI capabilities. You will take ownership across the full data lifecycle, from requirements definition to deployment and maintenance. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (BigQuery, Redshift or Snowflake), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design and maintenance, Experience with AWS, GCP or Azure cloud services, Ability to design and build data ingestion and processing pipelines, Experience working in Agile environment, Understanding of data governance and data quality concepts 📃 Skills: Python, SQL, Snowflake, BigQuery, Redshift, Databricks, Azure, AWS, GCP, Terraform, dbt, PowerBI, Spark, ETL, CI/CD 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project Data Foundation & AI Enablement Project Scope We are architecting a modern Data Platform for a fast-scaling client in the Insurance sector. Our work consolidates fragmented legacy systems, organises data from a vast number of sources, and establishes a standardised, governed, and future-proof data foundation. We aim to unlock the full value of the company’s data, enabling faster, informed decision-making and providing the backbone for business growth and AI readiness. Tech stack SQL, Python, Snowflake, dbt, Data modelling, Data quality, Power BI, Azure, Terraform Challenges The primary objective is to deliver a robust data foundation and enable AI capabilities for a client that has grown organically. The work focuses on several key areas: Establishing a production-ready, fully operational Snowflake environment and driving operational excellence. Translating complex business logic into accurate data models to ensure the platform truly reflects business reality. Integrating diverse data sources to build reliable data products and comprehensive data dictionaries. Managing the full Data Engineering and Data Science lifecycle to support production ML and AI experimentation. Taking ownership from concept to deployment. Cultivating an engineering mindset by promoting automation, CI/CD, and rigorous standards. Team We are building a small (4-6 people), agile, cross-functional team capable of delivering the complete data platform, from initial architecture to production operations. Roles involved: DevOps, Data Engineer, Snowflake Specialist, MLOps/AI Engineer, Business Analyst (BA). The team will collaborate closely with business stakeholders to ensure effective knowledge transfer and strict alignment with strategic goals. Team The team is small but highly motivated, taking on a broad scope of responsibilities as the platform is built and expanded. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now

🏢 Summary: The role focuses on building and scaling production-grade infrastructure and APIs to serve machine learning models, enabling data scientists to deliver robust, automated solutions to millions of users. You will design CI/CD pipelines, manage cloud infrastructure, and implement MLOps best practices to ensure reliable and scalable ML deployments. This position bridges data science and engineering, emphasizing DevEx, automation, and production readiness. 🗂️ Requirements: Extremely proficient in Python, Deep experience building and scaling APIs for ML model serving, Production experience with AWS, Proficiency in Docker and container orchestration, Experience with CI/CD tools (GitHub Actions, Jenkins), Proficiency with Terraform, Experience with Airflow or similar workflow tools, Familiarity with Tensorflow or similar ML frameworks, Experience in data science or data-focused software engineering, BA/BS in Computer Science, Math, Physics, Engineering, Statistics or related field, Fluency in SQL, Legal right to work in Poland 📃 Skills: Python, FastAPI, Flask, AWS, Docker, Kubernetes, GitHub, Jenkins, Terraform, Airflow, Tensorflow, PyTorch, SQL, CI/CD, MLOps, APIs 🏢 Description: We are looking for a technical powerhouse to bridge the gap between complex data science and scalable engineering . You will supercharge our Data Science team by building the automated infrastructure and APIs that deliver our models to millions of members, ensuring our recommendations are not just smart, but production-ready and bulletproof. About Secret Escapes Secret Escapes is the world's leading, members-only travel and experiences company. We inspire the world to escape by bringing hand-picked offers at unbeatable prices to millions of members worldwide. We’re backed by some of the smartest investors out there, including Google Ventures. Operating in 10 countries across Europe, Secret Escapes continues to grow and establish itself as a world-class business, dedicated to giving our members the best range and value in luxury travel deals at low prices. Secret Escapes operates a hybrid working policy and we are all in the office 3 days a week. This role will be based in our Travelist office in Poland. We offer flexible working with core hours between 10 am to 4 pm, and you have the freedom to schedule the remaining hours to suit your routine. In keeping with being an inspirational travel brand, we also have a ‘Work from Anywhere’ policy, so you can work from anywhere in the world for up to 4 weeks each year! This benefit is designed both to feed our travel passion and support parents and carers, especially during school holidays. We’re a diverse and inclusive bunch of individuals from different backgrounds and with varied interests, but the one thing we all have in common is that we’re good people (even if we do say so ourselves!). We are growing our Product, UX, and Engineering teams significantly. Come and grow with us. The Role & what you'll do Your main responsibility is to support a team of data scientists and ML Ops engineers to offer relevant inferences as an internal service. While our Data Scientists focus on experimentation, you focus on the Developer Experience (DevEx)—building the rails that allow them to ship value faster. You will act as the vital link, liaising with key stakeholders in Engineering, Data, and Product teams to ensure our machine learning capabilities are robust, scalable, and integrated seamlessly into the Secret Escapes platform. Day to day, you will be working on... Architecting and maintaining the CI/CD pipelines for our data products using GitHub Actions and Jenkins. Building, hosting, and scaling high-performance APIs (using frameworks like FastAPI or Flask) to serve ML models to our website and apps. Containerizing machine learning applications using Docker to ensure consistent deployment across our AWS environment. Orchestrating complex data workflows and pipelines using Airflow (or similar tools) to ensure data consistency and accuracy. Managing our Infrastructure as Code (IaC) using Terraform to ensure reproducible and scalable environments. Identifying opportunities to build and improve machine learning models , specifically focusing on the engineering challenges of deploying Tensorflow (or similar) models for recommendation and anomaly detection. Keeping yourself updated on new developments in your field of expertise, specifically regarding modern MLOps best practices and API design. The Team The team consists exclusively of Good Eggs. We care deeply about our customers, but also about each other. We are a creative bunch who prioritize ruthlessly. We work hard and have fun in equal measure. Must haves Extremely proficient in Python (development, scripting, and packaging). Deep experience building, hosting, and scaling APIs for ML model serving . Production experience with Cloud Infrastructure, specifically AWS. Proficiency in Containerization (Docker) and Orchestration. Solid experience with CI/CD tools, specifically GitHub Actions and Jenkins. Proficiency in Infrastructure as Code tools, specifically Terraform. Experience working with workflow management tools like Airflow. Familiarity with ML frameworks like Tensorflow (or PyTorch/similar). Solid experience in the data science field or software engineering with a data focus. BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical fields. Fluency in SQL. And you are... Detail oriented Analytical Pragmatic Able to communicate the results of analyses in a clear and effective manner Obsessed with automation and code quality A champion of "DevOps culture" within Data Science Insatiably curious We are an equal opportunity employer: Diversity and inclusion are important to us at Secret Escapes and we encourage a culture where everyone can be themselves at work. We value and actively seek out a richly diverse range of talent and our policies ensure that every job application and employee is treated fairly, with equal opportunity to succeed. All applicants will be considered for employment without regard to any characteristic protected by law. We love building diverse teams and welcome applications from talent across the globe. However, for this specific position, we are unable to sponsor work permits in Poland. We strongly encourage you to apply if: You already hold the legal right to work in Poland. You are eligible to secure your own independent right to work (e.g. through a non employer sponsored visa or residence title) If you need to explore independent visa routes, we recommend checking the official website of the Polish Office for Foreigners or your local Polish Consulate for the most accurate, up to date information.

🏢 Summary: The role involves end-to-end development and lifecycle management of machine learning models supporting credit risk assessment and fraud detection processes. You will design, deploy, monitor, and optimize predictive and decision models that directly impact business decisions and transaction security. The position requires strong expertise in financial risk or fraud modeling within production environments. 🗂️ Requirements: Minimum 2 years of experience building and deploying ML models in financial sector, Experience in credit risk or fraud detection modeling, Strong knowledge of risk modeling techniques, Experience building and deploying NLP models, Proficiency in Python, Experience with version control systems, Knowledge of SQL and databases, Experience working with large datasets, Experience with AWS and Snowflake 📃 Skills: Python, SQL, AWS, Snowflake, CatBoost, XGBoost, LightGBM, scikit-learn, Keras, TensorFlow, PyTorch, Git, NLP 🏢 Description: Dołączając do zespołu AI Risk & Compliance Models , będziesz odpowiadać za pełny cykl życia modeli predykcyjnych i decyzyjnych wspierających procesy oceny ryzyka oraz zgodności regulacyjnej. Obejmuje to m.in . modele oceny wiarygodności kredytowej klientów oraz systemy detekcji nadużyć (fraud detection). Twoją rolą będzie projektowanie, budowa, wdrażanie oraz ciągła ewaluacja modeli, które realnie wpływają na decyzje biznesowe i bezpieczeństwo transakcji. Doświadczenie w obszarze ryzyka lub fraudów (detekcja nadużyć) To kluczowy i niezbędny warunek – poszukujemy osoby, która pracowała z modelami ryzyka lub fraud detection i zna specyfikę tych obszarów. Zakres obowiązków Projektowanie, budowa i wdrażanie modeli uczenia maszynowego, ze szczególnym naciskiem na modele oceny wiarygodności kredytowej. Tworzenie modeli klasyfikacyjnych, regresyjnych i segmentacyjnych działających zarówno on-line, jak i off-line. Wykorzystanie różnorodnych technik ML, w tym modeli boostingowych, deep learningowych oraz rekomendacyjnych. Prowadzenie analiz eksploracyjnych i formułowanie rekomendacji dla obszarów biznesowych. Przetwarzanie dużych zbiorów danych z wykorzystaniem Snowflake i AWS. Tłumaczenie wymagań biznesowych na konkretne rozwiązania Data Science. Monitorowanie, utrzymanie i optymalizacja istniejących modeli. Dzielenie się wiedzą ekspercką z zespołem Data Science. Samodzielne prowadzenie projektów analitycznych oraz wdrażanie rozwiązań na środowiska produkcyjne. Kompetencje techniczne i funkcjonalne Minimum 2 lata doświadczenia w budowie i uprodukcyjnianiu modeli ML w sektorze finansowym – koniecznie w obszarze ryzyka kredytowego lub detekcji fraudów (MUST HAVE). Ekspercka wiedza w zakresie technik modelowania stosowanych w obszarze ryzyka oraz umiejętność przekładania złożonych zagadnień na zrozumiały język dla różnych grup odbiorców. Bardzo dobra znajomość algorytmów i metod ML (np. CatBoost, XGBoost, LightGBM, scikit-learn, Keras, TensorFlow, PyTorch). Doświadczenie w budowie i wdrażaniu modeli NLP. Biegła znajomość Pythona oraz narzędzi kontroli wersji (Git). Znajomość relacyjnych i nierelacyjnych baz danych oraz języka SQL. Umiejętność pracy z dużymi wolumenami danych. Doświadczenie w pracy z technologiami chmurowymi – szczególnie AWS i Snowflake. Umiejętność jasnej i przejrzystej komunikacji z interesariuszami biznesowymi. Benefity: Prywatna opieka LuxMed, bezpłatne badania profilaktyczne oraz masaże odciążające kręgosłup. Budżet na doposażenie stanowiska pracy zdalnej oraz vouchery podarunkowe. Śniadania w formie bufetu przygotowywane na miejscu. Wyjazdy integracyjne i rodzinne do prywatnego ośrodka nad jeziorem. Dofinansowanie karty Multisport.

🏢 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!