👉 Lead Data Scientist

🟣 You will be:

• designing and developing statistical models for property price adjustments across time, location, quality, and condition,

• building spatial algorithms (adaptive heatmaps, geographic clustering, polygon-based property search) to capture local market dynamics,

• implementing comparable property recommendation with feature engineering across different property types,

• developing market analysis pipelines with solid diagnostics: trend fitting, outlier detection, goodness-of-fit metrics,

• integrating LLM-based classification services for document and property analysis,

• exposing model outputs through production API endpoints and working with frontend engineers on data contracts,

• debugging models in production: edge cases, numerical issues, data quality problems.

🟣 Your profile:

• solid statistics background: regression, GAMs, mixed/random effects, link functions, robust estimation, outlier handling,

• proficiency in Python and the data science stack: NumPy, Pandas, statsmodels, SciPy, scikit-learn,

• experience building and maintaining production APIs with FastAPI and Pydantic,

• comfortable working with PostgreSQL and SQLAlchemy,

• familiar with containerized environments (Docker, Kubernetes, GCP),

• able to turn domain requirements into quantitative solutions and communicate trade-offs,

• good command of English (spoken and written),

• familiarity with basic statistical concepts (e.g., Bayes’ rule, linear regression, maximum likelihood estimation,

• practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.

🟣 Nice to have:

• geospatial data and libraries (GeoPandas, Shapely, H3, GeoAlchemy2),

• GAM libraries (PyGAM), JAX, or TensorFlow Probability,

• task queues and async workflows (Celery, Redis),

• observability tooling (OpenTelemetry),

• ML pipeline frameworks (Kedro),

• data validation and property-based testing (Pandera, Hypothesis, TestContainers),

• R integration (rpy2),

• LLM integrations (Google Gemini or similar),

• frontend awareness (React, TypeScript),

• real estate data, valuation methodology, or appraisal workflows.

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

🟣 Recruitment Process: CV review – HR Call – Interview – Client Interview – Decision

🎁 Benefits 🎁

✍ Development:

• development budget of up to 6,800 PLN,

• we fund certifications e.g.: AWS, Azure, ISTQB, PSM,

• access to Udemy, Safari Books Online and more,

• events and technology conferences,

• technology Guilds,

• internal training,

• Xebia Library,

• Xebia Upskill.

🩺 We take care of your health:

• private medical healthcare,

• multiSport card - we subsidise a MultiSport card,

• mental Health Support.

🤸‍♂️ We are flexible:

• flexible working hours,

• B2B or permanent contract,

• contract for an indefinite period.