Staff Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the complete lifecycle of ML models that enhance product experiences, coverage recommendation systems, user-to-channel routing, and agent assignment algorithms.

• Develop features, prototype experiments, and implement iterative model enhancements into production.

• Collaborate with engineering teams and product managers to determine how model scores are utilized in real-time product interfaces.

• Lead the product modeling roadmap.

• Contribute to the assessment of marketing effectiveness.

• Identify modeling opportunities proactively and rigorously evaluate assumptions.

• Convey uncertainty in actionable terms for stakeholders.

⛳️ Requirements

• Over 5 years of experience in data science or machine learning at established companies or rapidly growing technology firms.

• Solid understanding of supervised learning techniques and recommendation systems.

• Proven experience in deploying production models, rather than just working with notebooks.

• Proficient in Python, including libraries such as pymc, scikit-learn, and XGBoost/LightGBM.

• Expertise in SQL.

• Hands-on experience with Bayesian methods: prior elicitation, posterior inference, and experimental design.

• Experience with deploying production models that are integrated with consumer-facing applications.

• Excellent communication skills, with the ability to translate model behavior and uncertainty into actionable recommendations for stakeholders.

• Experience with recommender systems or personalization at scale.

• Knowledge of causal inference techniques such as difference-in-differences, uplift modeling, and instrumental variables.

• Familiarity with marketing mix modeling, media attribution, or measurement of incrementality.

• Background in insurtech, fintech, or other regulated sectors.

• Experience with dbt or data pipeline development.

• Familiarity with MLflow, feature stores, or other machine learning infrastructure tools.

• Capability to delve into details while maintaining a broader perspective.

• Ability to understand the trade-offs between simple heuristics and machine learning solutions, selecting the most suitable approach.

• Skill in aligning model performance metrics with business objectives and integrating multiple models into a cohesive solution.

• Commitment to elevating the team's data science standards through code reviews, documentation, and mentorship.

🏝️ Benefits

• Base salary ranging from $127,000 to $224,000 per year.

• Additional bonuses, equity, and benefits provided separately from the stated base salary.

• Details regarding US benefits are available on the Ethos careers page.