Data Scientist

📋 Description

• Define and build predictive models from scratch for churn, upsell, CLV
• Own the full modelling lifecycle: data from warehouse, feature engineering
• Deliver daily client-level scores integrated into CRM workflows
• Bridge data science and business: translate insights for non-technical teams
• Partner with sales leadership to design interventions using model predictions
• Present results to senior stakeholders

🎯 Requirements

• 4+ years of hands-on experience building and deploying predictive models on real business problems (classification, regression, scoring)
• Strong proficiency in Python (pandas, scikit-learn, XGBoost/LightGBM/CatBoost) and SQL
• Ability to independently frame ambiguous business problems as ML tasks — define target and features
• Experience with tabular data at scale: feature engineering, class imbalance, temporal validation, data leakage
• Ability to communicate model results to non-technical stakeholders
• Experience with time-series or event-based behavioral data

🎁 Benefits

• Competitive salary reflecting experience
• Flexible work from home or office mix
• Flexible benefits package
• Informal collaborative culture
• Ongoing training and education programs
• Global exposure with teams worldwide