Mid/Senior Data Scientist

🏢 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: 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: Data Science & Analytics role embedded within core business units (growth, product, AI, partnerships), owning end-to-end analytics, defining metrics, running analyses and experiments, and driving strategic decisions to scale the business from 5M to 50M customers. 🗂️ Requirements: 4+ years experience in consulting, investment banking, or high-growth technology company, Strong analytical skills with ability to independently pull, structure, and interpret data, Proficiency in SQL or Python, Experience owning ambiguous problems and delivering measurable impact, Ability to influence leadership through clear, data-driven communication 📃 Skills: SQL, Python, Clickhouse, Metabase, Jupyter, GitHub 🏢 Description: Why We’re Hiring Our Data Science & Analytics team has been a force multiplier and accelerant to our business, driving data and insights across product, growth, tech, and operations. As our business expands, we are hiring 4–6 team members to drive impact in Growth Marketing, Product Development, AI & Automation, and Strategic Partnerships. Why You Will (Or Won't) Like Working Here No slides: The only work that gets done is work that materially changes the trajectory of the business — important products, new growth channels, key metrics, and critical partner relationships. No corporate fluff: The team consists of analytical problem solvers who own critical domains. There is no bloat, unnecessary meetings, or waiting for approvals. Hands-on: This is not a pure strategy role. You will own execution, surface analytical insights, drive decisions, and see them through end-to-end. What You'll Own You will sit on the central Data Science & Analytics team and be embedded in one of the core business areas — growth, product, AI and automation, or strategic partnerships — owning the analytical function end-to-end. Define the right problems: Understand what business question an analysis answers and what decision it informs. Push back if the question is flawed. Data and insights: Define metrics, build reports, run analyses, design experiments, and surface insights that move key metrics. Drive outcomes: Present recommendations to product, growth, finance, or operations counterparts, explain what is happening and why, and define next steps. Who You Are First principles thinker: Break ambiguous problems into clear hypotheses before touching data. Comfortable with SQL or Python, and focused on solving the right problem. Direct communicator: Able to walk skeptical stakeholders through complex findings and gain buy-in. Write clearly and speak precisely. Owner: Take responsibility for outcomes and proactively fix problems, even outside your immediate scope. What You'll Bring 4+ years of experience at a consulting firm, investment bank, or high-growth technology company. Strong analytical skills with the ability to independently pull, structure, and interpret data. Track record of owning ambiguous problems and delivering impact. Clear, persuasive communicator who can influence leadership-level decisions. Our Tools SQL (Clickhouse), Metabase, Python, Jupyter Hub, GitHub. Compensation and Benefits Starting pay range: $150K - $170K, determined by skills, experience, qualifications, work location, and market conditions. Compensation may include equity grants. Comprehensive benefits package includes health, dental, and vision coverage, paid time off, paid parental leave, 401(K) plan with employer matching, wellness benefits, and other employee benefits. Equity opportunities may be part of the total rewards package. Part-time, contract, or freelance roles may not be eligible for certain benefits.

🏢 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: Long-term remote B2B opportunity for a Senior Data Engineer focused on building enterprise-scale data platforms, ETL/ELT pipelines, and Gen AI/LLM solutions for a US financial sector client. The role involves designing PoCs, developing production-grade applications, and working autonomously within an international team using AWS cloud and modern data engineering technologies. 🗂️ Requirements: Minimum 8 years of experience as Data Engineer, Strong Python skills, Strong SQL skills, Experience with ETL/ELT pipelines, Commercial experience with LLM projects, Experience in enterprise/global corporate environments, Very good knowledge of FastAPI, Very good knowledge of Airflow, Very good knowledge of AWS, Very good knowledge of Snowflake, Very good knowledge of Terraform, Very good knowledge of Neo4j, Very good knowledge of Jenkins, Very good knowledge of Docker, Experience with AWS cloud services, Experience with Data Warehouse solutions, Experience working with Docker, Airflow, Terraform or similar tools, Ability to work independently in enterprise environments, English proficiency at C1 level, Availability for 14:00–18:00 CET overlap with New York 📃 Skills: Python, SQL, ETL, ELT, LLM, FastAPI, Airflow, AWS, Snowflake, Terraform, Neo4j, Jenkins, Docker, Redshift, RDBMS, NoSQL, Matplotlib, Seaborn, Bokeh, Pandas, NumPy, scikit-learn 🏢 Description: Be in IT to firma rekrutacyjna, wyspecjalizowana w poszukiwaniu Specjalistów z branży technologii informatycznych. Obecnie, dla naszego klienta, poszukujemy osoby na stanowisko: AWS Senior Data LLM Engineer. Zakres obowiązków: Długofalowa współpraca z polską firmą IT, typu softwarehouse i outsourcing, specjalizująca się w dostarczaniu oprogramowania dla topowych organizacji finansowych, start-up'ów, funduszy i instytucji bankowych ze Stanów Zjednoczonych. Głównym celem roli jest projektowanie i wdrażanie systemów, wewnętrznych narzędzi oraz infrastruktury danych, które usprawniają procesy decyzyjne oparte na danych agregowanych z różnych źródeł — zarówno wewnętrznych, jak i zewnętrznych. Projekty mają silny komponent Gen AI/LLM, dlatego szukamy osoby, która nie tylko dobrze odnajduje się w klasycznym Data Engineeringu, ale też ma praktyczne doświadczenie z wykorzystaniem modeli językowych w realnych rozwiązaniach. Szukamy doświadczonego Senior Data Engineera, który dołączy do długoterminowego projektu realizowanego dla dużego klienta enterprise z USA z sektora finansów, inwestycji i real estate. Projektowanie i rozwijanie PoC z wykorzystaniem najnowszych technologii, w tym rozwiązań opartych o LLM i Gen AI. Eksperymentowanie z integracjami zewnętrznych narzędzi, API oraz źródeł danych. Współtworzenie i wdrażanie aplikacji produkcyjnych po zatwierdzeniu PoC. Budowanie narzędzi, rozwiązań i infrastruktury, które zwiększają samowystarczalność Data Scientistów oraz analityków biznesowych. Agregowanie, modelowanie i porządkowanie danych z wielu źródeł. Rozwój Data Lake, Data Warehouse oraz pipeline’ów ETL/ELT. Pracę z architekturą danych w środowisku enterprise. Szukanie nowych sposobów wykorzystania Gen AI w procesach biznesowych i analitycznych. Stack to między innymi: Python, FastAPI, Airflow, AWS Cloud, Snowflake, Terraform, Neo4j, Jenkins, SQL, Docker oraz dodatkowo Redshift, RDBMS, noSQL, Matplotlib, Seaborn, Bokeh, Pandas, NumPy, scikit-learn. Każdy projekt w większym lub mniejszym stopniu dotyka obszaru LLM/Gen AI — od integracji modeli, przez wykorzystanie danych semantycznych, po budowanie narzędzi wspierających analizę i podejmowanie decyzji. PoC trwają zwykle kilka miesięcy, a współpraca ma charakter długoterminowy. Współpraca z międzynarodowym zespołem, możliwe gapy w godzinach 14:00-18:00 polskiego czasu. Zespół pracuje bardzo autonomicznie. Klient dostarcza wymagania biznesowe, zespół doprecyzowuje zakres, projektuje rozwiązanie, dowozi PoC, a po jego zatwierdzeniu wdraża rozwiązanie produkcyjnie. Oczekujemy: Szukamy doświadczonego Senior Data Engineera, który dołączy do długoterminowego projektu realizowanego dla dużego klienta enterprise z USA z sektora finansów, inwestycji i real estate. Minimum 8 lat doświadczenia jako Data Engineer. Największy nacisk na oczekiwania to: mocny Python, SQL, ETL/ELT i koniecznie projekty w doświadczeniu, w których wykorzystywany był LLM oraz w pracy w środowisku, globalny, korporacyjnym. Bardzo dobra znajomość: LLM, Python, FastAPI, Airflow, AWS, Snowflake, Terraform, Neo4j, Jenkins, SQL, Docker. Mile widziana znajomość: Redshift, RDBMS, noSQL, Matplotlib, Seaborn, Bokeh, Pandas, NumPy, scikit-learn - nie oczekujemy znajomości tych technologii, ale z racji używania ich w projekcie, jest możliwość nauczenia się ich nawet od zera. Doświadczenie z AWS i usługami chmurowymi. Doświadczenie z Data Warehouse, szczególnie Snowflake. Doświadczenie w pracy z Dockerem, Airflow, Terraformem lub podobnymi narzędziami. Dojrzałość techniczną i seniorskie podejście do dowożenia rozwiązań. Umiejętność samodzielnej pracy w środowisku enterprise. Bardzo dobrą komunikację po angielsku — minimum C1, Gotowość do pracy z 4-godzinnym overlape’em z Nowym Jorkiem, najlepiej w godzinach 14:00–18:00 czasu polskiego. Oferujemy: Długofalowa współpraca B2B (kontrakt na czas nieokreślony) z wynagrodzeniem w przedziale 50-55 USD netto/godz. Brak płatnych urlopów. Wsparcie przy zakładaniu i prowadzeniu działalności gospodarczej, dla osób bez takiego doświadczenia. Sprawny proces rekrutacyjny - 90 minut rozmowy technicznej, następnie ok. 20 minut formalnej rozmowy z Hiring Managerem i decyzja. Współpraca w pełni zdalna. Benefity - Multisport/Medicover, licencje na AI toole, Claude, Cursor itp. Nowoczesny sprzęt zapewniany przez firmę, wraz z softem i konfiguracją. Spotkania integracyjne.

🏢 Summary: Senior Backend Developer (Python/Django) role in a SaaS platform for e-commerce analytics and process automation, focused on building scalable backend solutions that process large datasets and power pricing, ranking, and decision-support mechanisms. The position involves designing data-processing algorithms, integrating external APIs, and developing business logic in a fully remote, small product team. The offer provides high autonomy and real impact on product direction in a globally expanding platform. 🗂️ Requirements: Minimum 5+ years of commercial experience in Python, Very good knowledge of Django framework, Experience in designing algorithms and data processing solutions, Experience in implementing complex business logic, Experience with PostgreSQL, Experience with Elasticsearch, Experience with Redis, Ability to analyze large datasets, Experience with API integrations, Ability to work independently on complex technical problems 📃 Skills: Python, Django, PostgreSQL, Elasticsearch, Redis, API, Algorithms, DataProcessing, SQL, Git 🏢 Description: Jesteśmy agencją consultingową, zajmującą się wyszukiwaniem i pozyskiwaniem najlepszych talentów ✨ dla naszych klientów . Pomagamy start-upom, software house’om i przedsiębiorstwom w skalowaniu i transformacji poprzez nawiązywanie współpracy z ambitnymi inżynierami posiadającymi prawdziwą pasję do technologii. Obecnie poszukujemy Senior Backend Developera (Python\ Django) do polskiej firmy rozwijającej  międzynarodową platformę typu SaaS związaną z zarządzaniem, analityką i automatyzacją procesów dla e-commerce. Platforma jest narzędziem pobierającym informacje z dużych sklepów online, jak również z rynku ( m.in Google Shopping), i dostarcza dzięki temu analitykę oraz automatykę w zakresie polityk cenowych, zwiększania sprzedaży w określonych kategoriach, rynkach itd. Platforma jest łatwa w obsłudze dla użytkownika, ale pod spodem przetwarza duże zbiory danych i na ich bazie dostarcza szybko i inteligentnie wartościowe dane dla właścicieli sklepów. W obecnej fazie platforma wyprzedza już funkcjonalnie konkurencyjne rozwiązania a plany obejmują globalną ekspansję, głównie na rynki zagraniczne. Poszukujemy doświadczonego specjalisty, który zechce współtworzyć ten ekosystem produktowy i aplikację SaaS, ceni sobie posiadanie dużej autonomiczności 💪, wpływu na kierunek i sposób rozwoju firmy, pracę w małym, w pełni zdalnym i w 100% polskim zespole oraz szuka firmy nastawionej na wprowadzanie innowacyjności, w której panuje luźna atmosfera młodego zespołu . Szukamy osoby która pomoże w rozwoju modułów, integracji i sprawnym dostarczaniu biznesowych funkcjonalności. 🔷 Co będzie należało do Twoich głównych zadań? Rozwój backendu aplikacji w Pythonie i Django Projektowanie i implementacja algorytmów przetwarzania danych wykorzystywanych przez poszczególne moduły porównywarek. Rozwój oraz optymalizacja mechanizmów scoringowych, rankingowych i klasyfikacyjnych dla produktów dostępnych na platformie. Modelowanie logiki biznesowej oraz przekładanie złożonych wymagań biznesowych na wydajne rozwiązania techniczne. Analiza dużych zbiorów danych oraz budowanie mechanizmów wspierających automatyzację procesów decyzyjnych w systemie. Integracja systemu z zewnętrznymi platformami i usługami poprzez API Projektowanie i zarządzanie danymi w PostgreSQL, Elasticsearch oraz Redis. Tworzenie testów automatycznych oraz dbanie o jakość i stabilność dostarczanego oprogramowania. Współpraca bezpośrednio z CEO/CTO oraz zespołem produktowym przy realizacji nowych funkcjonalności. 🎯 Jakie skille, doświadczenie i mindset są przez nas poszukiwane? Minimum 5+ lat komercyjnego doświadczenia w programowaniu w Pythonie. Bardzo dobra znajomość frameworku Django. Silne umiejętności analityczne oraz matematyczne podejście do rozwiązywania problemów. Doświadczenie w projektowaniu algorytmów, przetwarzaniu danych oraz implementacji złożonej logiki biznesowej. Umiejętność modelowania procesów i zależności biznesowych w kodzie. Doświadczenie w pracy z PostgreSQL, Elasticsearch oraz Redis. Umiejętność samodzielnego rozwiązywania złożonych problemów technicznych. Chęć pracy w niewielkim, produktowym zespole oraz gotowość do głębokiego zrozumienia domeny biznesowej. Dobra organizacja pracy własnej i doświadczenie w pracy zdalnej. Nice to have Znajomość React i Next.js umożliwiająca pracę z warstwą frontendową. Mile widziane doświadczenie przy platformach e-commerce, porównywarkach, marketplace'ach, systemach rekomendacyjnych lub produktach opartych o scoring i analizę danych. ⭐ Co możemy Ci zaoferować ? W 100% pracę zdalną, z elastycznym podejściem Pracę z niewielkim, zgranym i doświadczonym zespołem Pracę w luźnym i dynamicznym start-upowym środowisku dofinansowanie do Multisport Nie czekaj! Aplikuj już teraz :)

🏢 Summary: Role for a Data Scientist responsible for end-to-end development and production deployment of ML models for dynamic pricing, recommendation, and offer-user matching at scale. The position focuses on building, optimizing, and monitoring learning-to-rank and deep learning models in real-time and offline environments. You will work with large datasets and modern cloud-based MLOps infrastructure to deliver production-grade AI solutions. 🗂️ Requirements: Minimum 2 years experience as Data Scientist or similar role, Strong knowledge of ML algorithms and Deep Learning, Experience with Learning-to-Rank models, Proficiency in Python, Experience with pandas, NumPy, scikit-learn, Experience with XGBoost or LightGBM or CatBoost, Experience with PyTorch or TensorFlow, Strong SQL skills, Experience with relational and non-relational databases, Experience working with large datasets, Experience with AWS, Experience with Snowflake, Ability to create data visualizations, Experience with Git, Experience with Jupyter Notebooks or JupyterLab 📃 Skills: Python, SQL, pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, TensorFlow, AWS, Snowflake, Snowpark, Plotly, Streamlit, Git, Jupyter, ML, DeepLearning, Learning-to-Rank, LLM, GenAI 🏢 Description: Trans.eu to jedna z największych platform logistycznych w Europie, łącząca tysiące przewoźników i zleceniodawców. W naszym zespole AI Matching & Pricing Models budujemy inteligentne systemy, które w czasie rzeczywistym dopasowują oferty, ustalają optymalne ceny i personalizują doświadczenia użytkowników - a to dopiero początek. Szukamy Data Scientist , który/a weźmie odpowiedzialność za pełny cykl życia modeli ML - od pomysłu, przez eksperymentowanie, po wdrożenie produkcyjne i ciągłą optymalizację. Co będziesz robić? Budować modele, które działają na produkcji - projektujesz, trenujesz i wdrażasz modele predykcyjne (pricing dynamiczny, rekomendacje, matching ofert i użytkowników) w skali tysięcy transakcji dziennie. Rozwijać systemy rekomendacyjne i ranking - tworzysz modele learning-to-rank, optymalizujesz kolejność i trafność wyników, budujesz embeddingi użytkowników i ofert w oparciu o dane behawioralne, kontekstowe i historyczne. Eksperymentować z najnowszymi podejściami - masz przestrzeń na testowanie rozwiązań opartych na deep learningu, szeregach czasowych, GenAI i LLM-ach do kontekstowych rekomendacji i profilowania użytkowników. Współpracować z zespołem MLOps - wspólnie dbasz o to, żeby modele działały stabilnie i skalowalnie zarówno w trybie online, jak i offline. Monitorować i optymalizować - ciągle ewaluujesz jakość prognoz i rekomendacji, identyfikujesz dryft i wprowadzasz usprawnienia. Eksplorować dane i komunikować wnioski - pracujesz z dużymi zbiorami danych, budujesz feature engineering, tworzysz wizualizacje i prezentacje dla interesariuszy. Czego oczekujemy? Min. 2 lata doświadczenia jako Data Scientist lub w pokrewnej roli. Solidna znajomość algorytmów ML, Deep Learning, Learning-to-Rank i najlepszych praktyk ich stosowania. Biegłość w Pythonie i ekosystemie Data Science (pandas, NumPy, scikit-learn, XGBoost/LightGBM/CatBoost, PyTorch lub TensorFlow). Swobodne pisanie SQL - doświadczenie z bazami relacyjnymi i nierelacyjnymi. Praktyka w pracy z dużymi zbiorami danych i środowiskami chmurowymi ( AWS, Snowflake ). Umiejętność tworzenia czytelnych wizualizacji (Plotly, Streamlit). Praca z Git i środowiskami typu Jupyter Notebooks / JupyterLab. Dodatkowe atuty Doświadczenie w budowie systemów personalizacji, matchingu lub rekomendacji . Praca z LLM-ami w kontekście generowania rekomendacji lub profilowania użytkowników. Znajomość Snowpark w ekosystemie Snowflake. Dlaczego warto? Realny wpływ - Twoje modele będą obsługiwać tysiące firm i setki tysięcy transakcji. To nie POC do szuflady. Pełna odpowiedzialność - prowadzisz projekt od eksperymentu po produkcję, bez sztucznych granic między „research" a „engineering". Nowoczesny stack - AWS, Snowflake, PyTorch, LLM-y, MLOps pipeline'y - pracujesz z technologiami, które mają znaczenie na rynku. Zespół, który ciągnie do przodu - otaczają Cię ludzie, którzy śledzą trendy w AI/ML i chętnie dzielą się wiedzą. Przestrzeń na rozwój - czas na eksplorację nowych podejść, udział w konferencjach i budowanie ekspertyzy w systemach rekomendacyjnych na dużą skalę. 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. Zagraniczne wyjazdy integracyjne w ramach workation. Dofinansowanie karty Multisport.

🏢 Summary: Software Engineer on the AI Data team responsible for building and scaling data collection and ingestion infrastructure to support large-scale model training. The role focuses on sourcing audio data, operating cloud-based pipelines on GCP, and collaborating with scientists to optimize dataset quality, cost, and throughput. This position directly powers next-generation AI models through petabyte-scale data engineering. 🗂️ Requirements: BS/MS/PhD in Computer Science or related field, 5+ years of software development experience, Proficiency in Bash scripting, Proficiency in Python, Experience working in Linux environments, Experience with Docker, Experience with Infrastructure-as-Code, Professional experience with at least one major cloud provider, Strong written and verbal communication skills 📃 Skills: Python, Bash, Linux, Docker, Terraform, GCP, Cloud, Infrastructure-as-Code, WebCrawlers, DataProcessing 🏢 Description: Overview We're looking to hire for our Data side of our AI team. This role is responsible for all aspects of data collection to support our model training operations. We build high-quality datasets at petabyte scale and low cost through tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us. What You'll Do - Be scrappy to find new sources of audio data and bring it into our ingestion pipeline - Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform - Collaborate closely with Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power next-generation models - Collaborate with the AI Team and Leadership to craft the dataset roadmap for next-generation consumer and enterprise products An Ideal Candidate Should Have - BS/MS/PhD in Computer Science or a related field - 5+ years of industry experience in software development - Proficiency with bash/Python scripting in Linux environments - Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (GCP used) - Experience with web crawlers and large-scale data processing workflows is a plus - Ability to handle multiple tasks and adapt to changing priorities - Strong communication skills, both written and verbal What We Offer - A fast-growing environment where you can help shape the company and product - An entrepreneurial-minded team that supports risk, intuition, and hustle - A hands-off management approach so you can focus and do your best work - An opportunity to make a big impact in a transformative industry - Competitive salary, bonus, and equity depending on experience - Opportunity to work on a product used by millions of people - Work at the intersection of artificial intelligence and audio

🏢 Summary: Backend engineering role focused on building scalable Python services and APIs for an AI platform used by enterprise customers. The position involves developing production backend systems, integrating AI components, and improving reliability in a collaborative engineering environment. Offers modern AI tooling, cloud-native development exposure, and growth opportunities within an AI-focused product team. 🗂️ Requirements: 2–5 years of backend application development experience, Python, REST APIs, Backend services, SQL, PostgreSQL, Asynchronous programming, Background job processing, AWS, Azure, GCP, Testing, Version control, AI development tools, English B2 📃 Skills: Python, FastAPI, Django, PostgreSQL, SQL, AWS, Azure, GCP, Docker, Redis, RabbitMQ, Kafka, TypeScript, REST, Git, CI/CD, ChatGPT, Copilot, Codex, Claude 🏢 Description: About Us Many companies want to use AI agents, but these agents often struggle with real business tasks. We solve this problem by building a platform that helps AI understand business rules, workflows, and processes. This enables AI to make better decisions and provide accurate, reliable, and trustworthy results. Our technology is used by leading companies across multiple industries to automate up to 85% of customer cases, reduce handling time by 20–25%, and complete tasks that previously took hours in just seconds. We work with leading technology partners and have been recognized for our innovative approach. Our mission is to help people everywhere get better answers through AI. About the Role We are looking for a Mid Backend Engineer to help build scalable backend services that power our AI platform. You'll work closely with experienced backend engineers, frontend developers, product managers, and platform engineers to develop new features, improve existing systems, and deliver reliable production software. This is a great opportunity to work on modern AI infrastructure while growing your technical skills in a collaborative engineering environment. Responsibilities - Build and maintain backend services, APIs, and background processing systems. - Develop scalable application logic using Python. - Collaborate with product managers and engineers to deliver new product features. - Integrate backend services with databases, external APIs, and AI components. - Monitor, troubleshoot, and improve production services. - Write clean, maintainable, and well-tested code. - Participate in code reviews and engineering discussions. - Improve development workflows using AI tools and automation. - Continuously learn from production feedback and contribute to improving system reliability and performance. Requirements - 2–5 years of experience building production backend applications. - Good knowledge of Python. - Experience building REST APIs and backend services. - Understanding of relational databases (PostgreSQL or similar) and SQL. - Familiarity with asynchronous programming and background job processing. - Basic understanding of cloud platforms such as AWS, Azure, or GCP. - Understanding of software engineering best practices, testing, and version control. - Good communication skills and willingness to collaborate across engineering and product teams. - Experience using AI development tools such as GitHub Copilot, Claude Code, ChatGPT, or similar. - English at B2 level or higher. Nice to Have - Experience with FastAPI, Django, or similar Python frameworks. - Experience working with Docker and CI/CD pipelines. - Familiarity with Redis, RabbitMQ, Kafka, or similar messaging technologies. - Experience building AI-powered applications or integrating LLM APIs. - Basic knowledge of TypeScript or frontend development. - Interest in distributed systems and cloud-native architectures. What We Offer - 20,000–24,000 PLN B2B (depending on experience). - Company stock options. - MacBook Pro. - Modern technology stack with opportunities to contribute to open-source projects. - Access to advanced AI development tools, including GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, and MCP Servers. - The opportunity to work on production AI systems used by enterprise customers. - A collaborative engineering culture focused on learning, ownership, and continuous improvement. - Career growth alongside experienced engineers in a fast-growing AI company. Our Culture and Values - Quality - We build reliable software with attention to detail and long-term maintainability. - Momentum - We move quickly, learn continuously, and improve through iteration. - Accountability - We take responsibility for our work and communicate openly. - Hard Work - We solve ambitious problems together and support each other along the way. - Learning Agility - We stay curious, embrace feedback, and continuously develop our skills. - Adapt and Thrive - We welcome change and see challenges as opportunities to improve. - Win Together - We collaborate, share knowledge, and succeed as one team.

🏢 Summary: Software Engineer on the AI Data team responsible for building and operating large-scale audio data ingestion pipelines to support model training. The role focuses on sourcing audio data, extending cloud infrastructure on GCP with Terraform, and collaborating with scientists to optimize cost, throughput, and data quality at petabyte scale. This position directly powers next-generation AI-driven consumer and enterprise products. 🗂️ Requirements: BS/MS/PhD in Computer Science or related field, 5+ years of industry experience in software development, Proficiency in Bash scripting, Proficiency in Python, Experience working in Linux environments, Experience with Docker, Experience with Infrastructure-as-Code concepts, Professional experience with a major cloud provider, Strong communication skills (written and verbal) 📃 Skills: Python, Bash, Linux, Docker, Terraform, GCP, Cloud, Infrastructure-as-Code, Web, Data, AI 🏢 Description: Overview We're looking to hire for our Data side of our AI team. This role is responsible for all aspects of data collection to support our model training operations. We build high-quality datasets at petabyte-scale and low cost through tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us. What You'll Do - Be scrappy to find new sources of audio data and bring it into our ingestion pipeline - Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform - Collaborate closely with Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power next-generation models - Collaborate with others on the AI Team and Leadership to craft the dataset roadmap to power next-generation consumer and enterprise products An Ideal Candidate Should Have - BS/MS/PhD in Computer Science or a related field - 5+ years of industry experience in software development - Proficiency with bash/Python scripting in Linux environments - Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (GCP) - Experience with web crawlers and large-scale data processing workflows is a plus - Ability to handle multiple tasks and adapt to changing priorities - Strong communication skills, both written and verbal What We Offer - A fast-growing environment where you can help shape the company and product - An entrepreneurial-minded team that supports risk, intuition, and hustle - A hands-off management approach so you can focus and do your best work - An opportunity to make a big impact in a transformative industry - Competitive salaries, bonus, and equity depending on experience - A friendly and laid-back atmosphere with a commitment to building a strong asynchronous culture - Opportunity to work on a product used by millions of people - Work in the fast-growing intersection of artificial intelligence and audio