Senior Data Scientist

Xebia is a global tech company with over 1,000 experts delivering work across cloud, data, and software. The company originated from two Polish companies, PGS Software and GetInData, and serves clients in fintech, e-commerce, aviation, logistics, media, and fashion sectors. Xebia is a trusted partner of Databricks, dbt, Snowflake, Azure, GCP, and AWS, and was the first AWS Premier Partner in Poland.

• Ready to join within 2 weeks
• Strong experience in applied data science and machine learning on real world datasets
• Solid understanding of ranking, optimisation, or recommendation problems
• Experience working with transactional and behavioural data
• Proficiency in Python for data analysis and model development
• Experience with experimentation, validation, and performance measurement of ML models
• Understanding of overfitting, bias, and model generalisation
• Ability to work closely with engineers to deploy models into production environments
• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery
• Exposure to Snowflake based analytics or ML workflows

Nice to have:

• Experience working in environments with business KPI guardrails such as margin, conversion, or NPS
• Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work

• Analysing large scale search, booking, and behavioural datasets to identify patterns impacting conversion, margin, and user relevance
• Designing, training, validating, and iterating machine learning models for ranking and recommendation use cases
• Developing margin aware, conversion aware, and relevance based scoring models aligned with defined business KPIs
• Experimenting with semantic relevance and embedding based approaches for intent driven search
• Defining features, evaluating data quality, and collaborating on feature readiness for ML training
• Running and interpreting offline evaluations and online experiments, including A/B testing and shadow mode validation
• Monitoring model performance, data drift, and retraining needs in production
• Collaborating closely with data engineers and platform engineers to productionise models and ensure scalability
• Documenting assumptions, results, and trade offs to support knowledge transfer and long term maintainability

Work from the European Union region and a work permit are required.