Data Scientist, LTV

Root was founded on the belief that car insurance is broken, and we set out to change it. We’re harnessing the power of technology to revolutionize this archaic, complicated industry. Using machine learning and mobile telematic platforms, we’ve built one of the most innovative insurtech companies in the world.

We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry.

Root is seeking a Staff Data Scientist I to lead the design, development, and oversight of the models that power our customer lifetime value ecosystem. This ecosystem includes hundreds of interdependent models and workflows covering conversion, retention, future premium, and claim losses. Its complexity and business importance require a deeply experienced data scientist who can guide and contribute to the team’s most challenging technical work while partnering directly with machine learning engineers on production deployment.

Lifetime value predictions shape some of Root’s most consequential decisions, driving millions of dollars in marketing investment, informing valuations for key business partnerships, and guiding insurance product decisions.

In this role, you will guide the technical work of the team’s data scientists and partner closely with machine learning engineers, data and software engineers, and business teams to improve decisions across Marketing, Finance, Product, and Customer Experience. You will also be a hands‑on individual contributor on that work.

This role carries broad technical responsibility for the quality and evolution of lifetime value modeling. You will resolve complex modeling questions and dependencies, evaluate enhancement opportunities, make principled tradeoffs, and establish practical standards for experimentation, validation, and monitoring. In partnership with the team manager, you will help shape quarterly priorities and longer‑term technical direction.

The ideal candidate combines deep modeling expertise and strong execution with the ability to improve the work of others. You can personally deliver complex analyses and models, exercise sound judgment across a highly complex ML system, and help develop other data scientists.

$171,400 - $214,200 (Eligible for competitive bonus and equity offering)

Root is a “work where it works best” company. Meaning we will support you working in whatever location that works best for you across the US. We will continue to have our headquarters in Columbus, Ohio.

• Own the technical direction of LTV modeling. Frame ambiguous problems, weigh analytical options, make principled tradeoffs, and change course as new evidence emerges.
• Improve the models that drive major decisions. Lead complex initiatives across interconnected conversion, retention, future-premium, and claim-loss models; understand how component models interact, diagnose underperformance, and prioritize improvements by business value.
• Keep a complex codebase healthy. Guide the design and evolution of the LTV codebase so it remains modular, tested, efficient, extensible, and readable as models and dependencies grow.
• Stay hands‑on across the lifecycle. Contribute directly to exploratory analysis, feature development, modeling, deployment, monitoring, and production support.
• Measure what matters. Design experiments and validation frameworks with clear success criteria, then evaluate model performance and business impact after launch.
• Help plan and deliver quarterly and long‑term priorities. Partner with the team manager to sequence work…