Engineering Manager, Data Science

• Deep ML experience: 6+ years building and deploying consumer-facing ML systems—recommendation engines, churn models, or similar. You've shipped models that ran in production at scale, not just notebooks. • Leadership experience: 2+ years leading or formally managing data scientists or ML engineers. You've built teams, not just participated in them. • Technical fluency: Strong Python skills; experience with Databricks or comparable ML platforms. Comfortable across the full lifecycle—experimentation, feature engineering, model training, deployment, monitoring. • Business orientation: Track record of translating ambiguous business problems into measurable ML solutions. You care whether the model moved the metric, not just whether it trained. • Pragmatic delivery mindset: You know when to ship an MVP to get feedback and when to invest in robustness. You edit scope ruthlessly rather than letting projects bloat. • An outcome-oriented and highly experimental interest in AI-driven development practices: You actively incorporate AI tools into your workflow and expect the same from your team. • Experience with experimentation platforms or causal inference methods • Background in subscription/SaaS businesses with retention and conversion challenges • Familiarity with TypeScript or production engineering practices • Equal Opportunity • We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.