Responsibilities

• Lead the development and advancement of ML models for bidding, targeting, and marketing optimization across paid search, lead aggregators, affiliates, direct mail, and emerging performance channels.
• Partner with Lifetime Value, Engineering, Marketing, and external vendors to translate business opportunities into scalable ML solutions.
• Set the technical direction of the Performance Marketing team by building and prioritizing a multi-quarter research roadmap spanning modeling, experimentation, and ML operations.
• Proactively identify and frame high-leverage opportunities across performance marketing, evaluate competing technical approaches, and prioritize investments.
• Mentor data scientists and MLEs in research design, ML model development, technical decision-making, and production engineering practices.
• Design and build production-ready ML systems while setting standards for maintainable code, reproducible research, automated testing, deployment, and operational reliability.
• Build monitoring frameworks for interconnected ML systems, enabling the team to detect model degradation, data issues, and changes in channel performance.
• Lead zero-to-one prototypes and introduce new modeling or ML operations capabilities that can reshape how Root allocates and optimizes performance marketing spend.

Requirements

• Advanced degree in a quantitative discipline (Master’s or PhD preferred) and 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 the ability to effectively communicate insights and technical concepts to both technical and non-technical audiences.
• Ownership mentality, with a demonstrated ability to take initiative, drive work forward, and mentor others.
• Strong communication skills, with the ability to translate complex technical concepts to non-technical stakeholders and influence strategic decisions.