At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all.
We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love.
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.
As a Principal Data Scientist at Root, you will serve as a high-impact technical leader driving forward our most complex and strategic quantitative pursuits. This role spans pricing, underwriting, and beyond—giving you wide latitude to shape experimentation, theory development, and applied research across the organization. You’ll help evolve Root’s core modeling strategy while incubating new capabilities in areas with emerging data science capabilities, such as agent distribution, policy and billing management, and customer service.
You will pair deep empirical and theoretical skill with a hands-on mentality. You’ll frequently review and elevate the work of experienced peers while also rolling up your sleeves to build prototypes, develop white papers, or challenge entrenched assumptions. You’ll be a cross-functional partner in designing systems and products with data science at their core.
Salary Range: $200,000 - $270,000
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.
How You Will Make an Impact
- Pioneer foundational modeling and research initiatives across a range of domains—including pricing, underwriting, agent/partnership strategy, and emerging business areas
- Challenge and reshape internal mental models—identify flawed assumptions or outdated conventions in how Root approaches modeling, and guide teams toward clearer, more robust alternatives
- Identify when modeling rigor is slipping (e.g., overfitting to internal consensus, inadequate evaluation), and intervene to restore discipline and clarity
- Go deep in unlikely places—select messy, ignored, or under-owned parts of the business where modeling could drive transformative value, and take the first real shot at formalizing them
- Communicate findings and perspectives clearly and forcefully to diverse audiences, from technical peers to senior executives
- Act as a thought partner to senior leadership on modeling strategy, experimentation frameworks, and long-term research architecture
- Collaborate closely with cross-functional teams to ensure alignment and synergy across departments on a multi-year horizon
- Drive adoption of modern best practices in statistical modeling, empirical validation, applied machine learning, and generative AI adoption
What You Will Need to Succeed
- Advanced degree (PhD or Master’s) in a quantitative discipline such as statistics, economics, applied mathematics, computer science, or a related field
- 10-15+ years of experience applying advanced statistical and machine learning methods to real-world problems, with a strong track record of impactful and paradigm-altering work
- Experience in a Principal or Staff-plus role at a high-performing, analytically mature organization
- Demonstrated success launching or leading net-new modeling initiatives, products, or research domains within an organization
- Ability to oscillate between strategic oversight and deep individual contributor work as needed
- Exceptional ability to reason from both theory and data, and to assess and strengthen the work of others through that lens; a radar for when someone is confidently wrong
- Strong verbal and written communication skills, with a proven ability to influence diverse technical and non-technical audiences
- Expertise in Python or R, SQL, and modern data science tooling; comfort with cloud-based infrastructure (e.g., AWS, GCP) and scalable modeling workflows
As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.
Top Skills
What We Do
At Root, we’re doing things differently. We’re reimagining the services people need so that they serve them better. And we’re doing it by using data, technology, and rapid innovation to create products and experiences that are fair, easy, personal, and affordable.
We’ve partnered with Carvana in a partnership that brings an industry-leading, seamless insurance process to the online car buying experience.
The launch of Carvana Insurance Built with Root delivers an elevated customer experience made possible through a deep integration that pre-fills key customer information so that a customer can skip data entry and jump directly to evaluating quotes and customizing coverage. This fully embedded product experience—from quote to payment—happens entirely within the Carvana checkout process. Teams from both Carvana and Root have worked for months to build this bold technology platform. An early iteration involved 24 screens in the customer experience flow—that experience is now just three straightforward steps.
Why Work With Us
Our success is because of the hard work, ingenuity, and exceptional performance of our team. People come to Root because they know they can make an impact in their role, the company, and the industry. We’re passionate and curious self-starters, building a top-notch customer experience. Sound like something you’d like to be a part of?
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