Data Scientist - Product Catalog Data w Poznań, Polska

Our team drives the solutions that build a trustworthy marketplace. As a collaborative group of Data Scientists, Data Engineers, and Analysts, we develop the statistical models, products and business rules necessary to analyze and continuously enhance our Product Catalog. We oversee the quality and correctness of all product components: titles, descriptions, images, and parameters. Our scope also covers ensuring consistency with sellers offers, automated products duplicates detection, building selection models and more. We work in close collaboration with developers and business teams, participating in the entire project lifecycle - from ideation through to implementation. Our ultimate goal is to create a single, reliable source of truth that powers a professional shopping experience for buyers and a fair, frictionless environment for our partners. Important things 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. Our team is mostly based in Poznan and Warsaw. What will your job involve? Co-creating projects on each stage - from concept to productization - to deliver insights and models solving actual business problems Using a wide range of model modeling techniques, including gradient boosting, Bayesian methods, causal inference, optimization, deep learning, and Generative AI (LLMs, Agentic AI) Working hand-in-hand with our Data Engineers who support the heavy-lifting of data processing on GCP Working closely with Analysts, PMs, and Developers to ensure the solutions you build integrate seamlessly into broader initiatives Leveraging diverse data types, moving beyond tabular data to extract value from spatial data, natural language (NLP), images, and time series Taking part in implementations of both offline and online models Engaging in brainstorming sessions, active knowledge sharing, and continuous professional development 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 You will be part of large-scale initiatives by proactively proposing and developing solutions, rather than simply executing predefined tasks 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 You’ll be a great fit if you bring: Hands-on Spark experience - You have experience working with Spark or PySpark. Since we deal with massive datasets, this is a must-have for our daily operations. An MLOps & deployment mindset - You don't just build models to sit on a laptop - you love seeing them go live. You have practical experience building automated pipelines and successfully deploying models into production environments. Solid software engineering habits - Python is your go-to language. You write clean, object-oriented code (classes, clean functions, and unit tests) and feel confident navigating and understanding large, complex repositories. Strong Data Science foundations - You have a deep understanding of statistics and machine learning. You know how to choose the right models, evaluate their performance properly, and calculate sample sizes accurately. Enthusiasm for GenAI & Agentic AI - You are excited about the future of AI and already use it to supercharge your daily workflow. You have a good theoretical and practical understanding of GenAI principles (prompting, validation) and love using coding assistants (like Copilot) smartly and critically. Great communication & business sense - You can naturally bridge the gap between tech and business. You are skilled at turning a business challenge into a clear ML problem and explaining complex technical results in a simple, intuitive way to stakeholders. A relevant background - You hold a degree in a quantitative field (such as Mathematics, Physics, Computer Science, Economics) OR have equivalent, solid hands-on experience in Data Science and Machine Learning roles. Bonus points if you have: Experience with Airflow: If you already know how to use Apache Airflow for pipeline orchestration, that’s a big plus! 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. Long term discretionary incentive plan based on https://jobeax.com/link/eExv7EVwvUxnOkx6 shares (restricted stock units). 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!