Teams at Ethos

Owns the infrastructure and production lifecycle for product and marketing machine learning models. Responsibilities include real-time model deployment, feature pipelines and stores, monitoring and alerting, CI/CD, retraining infrastructure, marketing model operationalization, data pipelines, ad-platform feedback loops, and dependency management. The role bridges data science and engineering while mentoring teammates and making pragmatic architecture decisions.

Own the product modeling roadmap and end-to-end lifecycle of production machine learning models, including recommenders, routing, and agent assignment. Engineer features, design experiments, deploy iterative improvements, and define real-time model integration with engineering and product teams. Apply Bayesian methods, causal inference, and marketing measurement while translating uncertainty into business recommendations. Mentor teammates and raise data science standards through code review and documentation.

Lead sales agent onboarding, ramp, skills training, coaching, and remedial development across direct-to-consumer sales teams. Build training curricula, refine scripts, analyze AI-generated call insights, run script experiments, enable managers, and translate product and sales-floor feedback into actionable training. The role requires hands-on facilitation, sales acumen, autonomous program building, and continuous measurement and improvement of agent performance.