Data Scientist

📋 Description

• Define and build predictive models for churn, upsell, and CLV.
• Work with trading, transactional, and behavioral data; engineer features.
• Own the full modeling lifecycle: target definition, training, validation, monitoring.
• Deliver daily client-level scores integrated into CRM workflows.
• Translate model outputs into actionable insights for non-technical sales teams.
• Collaborate with sales leadership to design interventions and present results.

🎯 Requirements

• 4+ years building and deploying predictive models (classification, regression, scoring)
• Strong Python (pandas, scikit-learn, XGBoost/LightGBM/CatBoost) and SQL.
• Frame ambiguous problems as ML tasks; define targets; engineer features.
• Experience with tabular data at scale: feature engineering, class imbalance, validation.
• Ability to communicate model results to non-technical stakeholders.
• Experience with time-series or event-based behavioral data.

🎁 Benefits

• Flexible benefits package.
• Work-from-home, office, or hybrid options.
• Collaborative, informal culture.
• Ongoing training and development.
• Global exposure with teams worldwide.
• Company-sponsored events and networking.