Junior Data Scientist

#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!

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.

• The salary range for this position depending on the skill set is as follows (contract of employment, tax-deductible cost):

• PLN 11 200 - 15 250

• Annual bonus based on your annual performance and company results.

• Our team is based in Warsaw.

What will your job involve?

• Creating data science projects at each stage - from concept to productization - to deliver models solving complex business problems.

• Developing ML models to monitor and continuously improve the quality of product mappings for key internal processes.

• Working with diverse data modalities, including tabular data, natural language text, product metadata, and time series.

• Building and experimenting with AI Agents designed to detect market trends and feed actionable intelligence directly into partner-support workflows.

• Identifying and building curated lists of market-relevant products crucial for buyers and platform competitiveness.

• Developing advanced data science solutions and predictive insights to empower business teams and drive strategic decision-making.

• Working hand-in-hand with Data Engineers who support data pipeline heavy-lifting on GCP.

• Cooperating closely with cross-functional stakeholders: business teams, product managers, data engineers, and analysts.

Our offer is addressed to people who:

• Have foundational experience or academic background in building classical ML/DS solutions (such as regression, classification, clustering, time series) and data analysis using SQL.

• Understand classical ML algorithms, their strengths, weaknesses, and basic hyperparameter tuning techniques.

• Know how to evaluate model performance using statistical metrics and diagnose basic data & mapping quality issues.

• Can explore data effectively by writing cost-efficient SQL queries, aggregating data, and creating clear reports or visualizations to deliver actionable business insights.

• Are capable of ingesting, validating, and transforming tabular data and product metadata into features ready for modeling.

• Can map business challenges (e.g. product relevance, mapping accuracy, trend detection) into analytical/modeling problems.

• Write readable, clean Python code following standards and best practices, with awareness of basic testing (e.g. unit tests) and cloud cost optimization basics.

• Possess practical and theoretical knowledge of Generative AI & Agentic AI principles (prompting, validation, agent workflows) and enthusiastically leverage AI-assisted coding tools (e.g. Copilot) to accelerate daily work.

• Communicate clearly and proactively, presenting findings and insights effectively to technical and non-technical stakeholders.

• Speak English and Polish at a B2+ level or higher.

• Graduated with a degree in Mathematics, Computer Science, Economics, Physics (or similar quantitative field) or have early-career experience in Data Science / Data Analytics positions.