Teams at Ethos

Develop financial and operational plans, including revenue, cost, and headcount targets; analyze unit economics, business expansion, and strategic initiatives; monitor financial performance metrics; and provide data-driven decision support to executive and cross-functional teams. The role also improves corporate finance processes, champions analytics, and collaborates with Product, Marketing, and Operations.

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.