Senior Data Scientist, Retention & Product

Responsibilities

• Churn & retention modeling
• Build churn/survival models and lifecycle-state models that flag at-risk customers early and anticipate where each customer is heading.
• Intervention & reason understanding: Power the retention interventions that act on that risk — save flows, skip/pause deflection, lifecycle messaging — and classify why customers churn so the response fits the reason rather than being generic.
• Resurrection & win-back
• Develop propensity models and personalized experiences that bring churned customers back.
• Personalization & Next-Best-Action: Decide the right action, offer, and message per customer across product surfaces, with an uplift layer measuring incremental impact.
• Offer & promo optimization: Determine who gets an incentive, when, and at what value — maximizing retained revenue without over-discounting.
• Production & MLOps
• Own the full model lifecycle and ship models into the systems where they act; handle monitoring, retraining, and drift.
• Experimentation & incrementality

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