CURRENT ROOT EMPLOYEES - Please apply using the career page in Workday. This career site is for external applicants only.

The Opportunity

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.

Join our Lifetime Value (LTV) team as a Lead Data Scientist I to improve how Root models customer value and uses it to inform decisions across the customer lifecycle. In this role, you’ll contribute to both predictive and scenario-based modeling to help forecast outcomes, evaluate business strategies, and support long-term planning.

You'll deepen Root's understanding of how key decisions in pricing, marketing, and customer experience influence lifetime value. Working closely with cross-functional partners, you'll build scalable tools and frameworks that support experimentation, risk assessment, and uncertainty quantification—empowering smarter, more consistent decision-making throughout the company.

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 to give more flexibility and more choice about how we live and work.

Salary Range: $140,000 - $175,000 (Bonus and LTI Eligible)

How You Will Make an Impact

• Develop LTV models that quantify customer value across channels and customer segments to influence strategic decisions across the company

• Build simulation tools to assess the impact of product changes on customer behavior and business outcomes

• Identify new data and modeling techniques to improve model accuracy and customer segmentation

• Continuously monitor model performance, refine evaluation methods, and respond quickly to emerging trends

• Collaborate with cross-functional partners to align modeling priorities with business needs and produce actionable results

• Improve automation, reproducibility, and maintainability of existing modeling workflows

What You Will Need to Succeed

• Advanced degree in a quantitative discipline (PhD preferred) and 5+ years of applying advanced quantitative techniques to problems in industry

• Expertise in Python, SQL, and modern data science workflows (version control, cloud environments, etc.)

• Demonstrated success in building models that drive business impact—forecasting, simulation, or causal inference experience strongly preferred

• Excellent communication skills: conveys complex analyses and insights clearly to both technical and non-technical audiences

• Ability to consider problems from first principles, combining critical thinking with domain knowledge to navigate ambiguity

• Ownership mentality: takes the initiative to identify, champion, and execute on the highest impact work

Don’t meet every single requirement?

Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Root, Inc., we are dedicated to building a diverse and inclusive workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway!

Join us

At Root, we judge people based on the merit of their work, not who they are. If you are passionate about what this role entails and solving real problems, we encourage you to apply. We want to learn about you and what you can add to our team.

Who we are

We’re harnessing the power of technology to revolutionize insurance. Using machine learning and mobile telematic platforms, we’ve built one of the most innovative FinTech companies in the world. And we’re just getting started.

What draws people to Root

Our success is in large part due to our unwavering standards in hiring. We recognize that our products are only as good as the people building and promoting them. We want individuals who find solutions by going through the cycle of ideation to implementation with curiosity, rigor, and an analytical lens. Ask anyone who works here and you’ll hear similar reasons for why they joined:

Autonomy—for assertive self-starters, the opportunities to contribute are limitless.

Impact—by challenging the way it’s always been done, we solve problems that have a big impact on our business.

Collaboration—we encourage rich discussion and civil debate at every turn.

People—we are inspired by the collection of crazy-smart people around us.