Data Scientist – Applied Analytics

About the role

We are looking for a Data Scientist to work on applied analytics and practical ML models that support business decisions. The role focuses on independent work in SQL and Python to prepare data, build user segmentation, campaign analysis, and predictive solutions in close collaboration with Data Analysts.

Key responsibilities

• Prepare datasets from the data warehouse using SQL and develop features for segmentation and predictive models.
• Build and validate practical ML models (e.g., churn, propensity, campaign scoring) with clear business interpretation.
• Support user segmentation, campaign ROI analysis, and effect measurement together with Data Analysts.
• Analyze products and benefits to improve retention, engagement and monetisation.
• Monitor model quality and usefulness in real business processes.
• Collaborate on data quality, reproducibility and provide inputs for business presentations.

Required profile

• Minimum 2 years of relevant experience.
• Strong SQL skills (complex joins, window functions, aggregations, optimization, data cleaning).
• Proficiency in Python (Pandas, NumPy) and modeling libraries such as Scikit‑Learn, XGBoost or PyTorch/TensorFlow.
• Understanding of how models and segments are used in business contexts like campaigns, CRM and KPI tracking.

Required skills

• SQL
• Python
• Pandas
• NumPy
• Scikit‑Learn
• XGBoost
• PyTorch
• TensorFlow

What we offer

• 22–26 days of annual leave.
• 38‑hour working week with flexible hours.
• Hybrid working model.
• Private health insurance and mental health initiatives.
• Open feedback culture.
• Career development program and training opportunities.