Staff Data Scientist

Ethos

. Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders, user-to-channel routing, and agent assignment logic .

Posted 11/3/2026full-timeRemote • United StatesLead💰 $127,000 - $224,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning model development and deployment, with a strong focus on supervised learning, recommendation systems, and causal inference. Proficient in translating complex model behaviors into actionable insights for stakeholders while aligning model performance with business objectives.

Highest-signal resume keywords

Machine Learning Model DevelopmentSupervised LearningPython ProficiencyBayesian ExperienceProduction Model Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Supervised LearningRecommendation SystemsCausal InferenceMarketing Mix ModelingSQLPythonPymcScikit-LearnXGBoostLightGBM

Soft Skills

Strong Communication SkillsMentorshipDetail-OrientedStakeholder Engagement

Tools & Technologies

MLflowFeature StoresDbtData Pipeline

Industry Keywords

InsurtechFintechRegulated Industries

Tech Stack

Tools & technologies

PythonScikit-LearnSQL

About the role

Key responsibilities & impact

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 product managers to define how model scores are consumed in real-time product surfaces
Own the product modeling roadmap
Contribute to marketing measurement
Define modeling opportunities proactively and stress-test assumptions
Communicate uncertainty in actionable terms for stakeholders

Requirements

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
Experience shipping production models, not just notebooks
Proficiency in Python, including pymc, scikit-learn, XGBoost/LightGBM
Proficiency in SQL
Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
Experience deploying production models integrated with consumer-facing products
Strong communication skills; ability to translate model behavior and uncertainty into stakeholder recommendations
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
Ability to get into details without losing the bigger picture
Ability to understand tradeoffs between simple heuristics and ML solutions and select the appropriate approach
Ability to align model performance metrics to business objectives and combine multiple models into a coherent solution
Ability to raise the team's data science bar through code review, documentation, and mentorship

Benefits

Comp & perks

Base salary of $127,000–$224,000 per year
Applicable bonus, equity, and benefits are provided separately from the listed base salary
US benefits details available through Ethos careers page