Data Scientist

Develop Customer Lifecycle Intelligence: Lead the development of predictive models for Customer Lifetime Value (CLV), churn or buying propensity, and behavioral segmentation to drive marketing campaigns.

Optimize Experimental Design: Design and implement A/B testing and Causal Inference roadmap, ensuring rigorous statistical validation for incrementality testing and lift studies.

Technical Excellence & Code Standards: Conduct rigorous peer reviews of Python/SQL code and ensure the scalability of ML pipelines in production (MLOps).

Stakeholder Influence: Translate technical model outputs into actionable "Growth Levers" for the CMO and Product heads, aligning data science initiatives with marketing targets.

Communication: Excellent communication, both verbal and written is a must.

Technical skills:

• Experience with statistical and ML models, for both supervised and unsupervised learning. Hands-on expetise in Python and SQL is required. Knowledge of working in cloud platforms and familiarity with MLOps.
• 5+ years of professional experience in Data Science, with at least 2 years focused specifically on Marketing or Consumer Analytics.
• Proven track record of leading or working through the full data product lifecycle (from ideation to production).
• Master’s or PhD in a quantitative field (Statistics, Economics, Computer Science, or Mathematics).