Data Scientist – Python & Cloud Data Platforms (f/m/x)

Technologies we use

About the project

Your responsibilities

• Translate business problems into analytical solutions: define hypotheses, choose metrics, and select the right modeling approach for the question at hand
• Explore, clean, and prepare data using Python (pandas, NumPy), working with structured and semi-structured sources of varying quality
• Build, validate, and tune machine learning models for classification, regression, forecasting, segmentation, and recommendation using scikit-learn, XGBoost, and statsmodels
• Design and analyze experiments: A/B tests, statistical hypothesis testing, and causal analysis that hold up to scrutiny
• Work hands-on with enterprise data platforms such as Microsoft Fabric (lakehouses, notebooks, semantic models) and Palantir Foundry (pipelines, ontology, operational workflows)
• Communicate findings through clear visualizations, dashboards, and narratives tailored to technical and non-technical stakeholders alike
• Collaborate with data engineers on data availability and quality, and with ML/AI engineers to move models from notebook to production
• Monitor deployed models for drift and degradation, and own the retraining and improvement cycle

Our requirements

• At least 4 years in data science or applied analytics, with models and analyses that made it past the prototype stage
• Strong Python skills across the standard data stack (pandas, NumPy, scikit-learn)
• Solid statistical foundations: hypothesis testing, regression, experimental design, and knowing when a result is real versus noise
• Knowledge of at least one cloud/data platform and its data science components — Azure (Microsoft Fabric, Azure Machine Learning), AWS (SageMaker), GCP (Vertex AI, BigQuery ML), Snowflake (Snowpark ML, Cortex), Databricks (MLflow, Mosaic AI), or Palantir (Foundry Code Workspaces, Foundry ML, AIP)
• Ability to communicate analytical results clearly to business stakeholders and influence decisions with data
• Familiarity with working autonomously while collaborating effectively with data engineers, architects, and product teams
• Fluent English, both written and spoken
• Fluent Polish required
• Residing in Poland required

Optional

• Production experience with Microsoft Fabric or Palantir Foundry certification (Foundry Data Engineer / Data Scientist tracks)
• Experience with time series forecasting, NLP, recommender systems, or exposure to LLM-based workflows
• Familiarity with MLOps practices: MLflow, experiment tracking, model versioning, and CI/CD for ML
• Experience with Power BI or other BI tools, and distributed processing with Spark/PySpark