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Salary: USD 171,400 - 214,200 / annual
Root Insurance is revolutionizing car insurance through machine learning and mobile telematic platforms. The Quantitative Science team owns marketing capital allocation across distribution channels, using quantitative methods to optimize strategies.
As a Staff Data Scientist I on the Performance Marketing team, you will lead research on lead segmentation and bidding optimization to drive marketing profitability. You'll design and execute research programs, expand modeling capabilities, and deliver high-impact solutions into production. As a thought leader, you'll mentor peers and model best practices for rigorous, production-ready work.
Key responsibilities include:
- Lead development and advancement of ML models for bidding, targeting, and marketing optimization across paid search, lead aggregators, affiliates, direct mail, and emerging channels
- Partner with Lifetime Value, Engineering, Marketing, and external vendors to translate business opportunities into scalable ML solutions
- Set technical direction of the Performance Marketing team by building and prioritizing a multi-quarter research roadmap
- Proactively identify high-leverage opportunities, evaluate competing technical approaches, and prioritize investments
- Mentor data scientists and MLEs in research design, ML model development, technical decision-making, and production engineering
- Design and build production-ready ML systems while setting standards for maintainable code, reproducible research, automated testing, and deployment
- Build monitoring frameworks for interconnected ML systems to detect model degradation, data issues, and channel performance changes
- Lead zero-to-one prototypes and introduce new modeling or ML operations capabilities
- Engage regularly with cross-functional departments and executive team
Requirements:
- Advanced degree in a quantitative discipline (Master's or PhD preferred)
- 8+ years of experience applying advanced quantitative techniques in industry
- Demonstrated leadership in developing and deploying real-time models, emphasizing automation and innovation
- Expert-level Python skills, including data querying, manipulation, and modeling
- Extensive experience developing and applying advanced ML models, particularly ensemble methods
- Skilled in version control (e.g., Git) with experience contributing to large-scale, collaborative projects
- Hands-on experience with AWS tools (e.g., EC2, SageMaker, Redshift) or equivalent platforms for scalable compute and storage
- Excellent business intelligence and visualization skills, with ability to communicate insights to technical and non-technical audiences
- Ownership mentality with demonstrated ability to take initiative, drive work forward, and mentor others
- Strong communication skills to translate complex technical concepts to non-technical stakeholders and influence strategic decisions
