Senior Data Scientist

Responsibilities

• Build, deploy, and iterate on customer churn prediction models
• Identify leading indicators, segment at-risk cohorts, and work with Customer Success on retention playbooks
• Develop propensity models and next-best-action recommendations to help commercial teams prioritise accounts and product conversations
• Design attribution frameworks across marketing channels, sales motions, and product touchpoints
• Build the data products that let leadership see what's actually driving revenue
• Design and analyse A/B tests and quasi-experiments for commercial initiatives
• Take models from notebook to production
• Translate ambiguous commercial questions into well-scoped analytical problems
• Communicate findings clearly to non-technical audiences

Requirements

• 5+ years in applied data science, with experience on commercial problems (churn, LTV, propensity, attribution, pricing, or similar)
• Strong SQL and Python (pandas, scikit-learn, statsmodels)
• Comfortable building production-grade code, not just notebooks
• Hands-on experience with Snowflake (or a comparable cloud data warehouse)
• Experience deploying models on AWS (SageMaker, Lambda, ECS, or similar)
• Solid grounding in statistics, experimentation, and causal inference
• Track record of shipping models that are actually used by the business
• Excellent communication skills