Overview
Own the product modeling roadmap for Ethos's ML models and contribute to marketing measurement, designing, building and deploying production ML models in partnership with PMs.
What you'll do
- Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders, user-to-channel routing, and agent assignment logic
- Engineer features, prototype experiments, and ship iterative model improvements to production
- Work with engineering and PMs to define how model scores are consumed in real-time product surfaces
What you'll need
- 5+ years in data science or ML at established firms or high-growth tech
- Strong command of supervised learning and recommendation systems; you've shipped production models, not just notebooks
- Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL
- Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
- Experience deploying production models integrated with consumer-facing products
- Strong communication skills; able to translate model behavior and uncertainty into stakeholder recommendations
- Bias toward ownership; you identify what needs to be built before anyone files a ticket
Nice to have
- Recommender systems or personalization at scale
- Causal inference: diff-in-diff, uplift modeling, instrumental variables
- Marketing mix modeling, media attribution, or incrementality measurement
- Experience in insurtech, fintech, or other regulated industries
- dbt or data pipeline experience
- MLflow, feature stores, or other ML infrastructure tooling
- Gets in the weeds without losing the bigger picture
- Knows the tradeoffs between simple heuristics and ML solutions and picks the right tool for the job
- Aligns model performance metrics to business objectives and combines multiple models into a coherent solution
- Raises the team's data science bar through code review, documentation, and mentorship
Details
- Full-time position
- Remote, US
- US national base salary range: $127,000 - $224,000 (base salary only; excludes bonus, equity, and benefits)
Read the full description and apply on the company’s own careers page.