Lead Data Scientist, Marketing

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.

At Root, the Quantitative Science team owns the majority of all marketing capital allocation, using quantitative methods to test, maintain, and enhance our marketing strategies across numerous distribution channels. As a Lead Data Scientist in Marketing Research, you'll help shape Root's mid and upper-funnel marketing strategy to drive profitable growth. You'll use predictive models to identify and segment high-value audiences, and apply statistical techniques to measure creative and campaign performance. You will lead the design and execution of marketing campaigns while crafting strategies to drive greater marketing efficiency. This role bridges data science, marketing strategy, and experimentation to help us uncover how and where Root's investments generate true incremental growth.

This role is heavily focused on marketing activation, including onboarding new vendors, quantifying channel value, and executing high-impact marketing campaigns. The position will center on improving the performance of Root's mid and top of funnel marketing campaigns while exploring and testing new vendor partnerships. You'll also lead efforts to measure and optimize creative performance across campaigns, developing insights that inform message design, targeting, and delivery. Over time, you'll build a deep understanding of partner platforms and their optimization levers, helping Root maximize efficiency and effectiveness across our marketing ecosystem.

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

How You Will Make an Impact

• Expand and diversify Root's direct marketing portfolio by shepherding new mid-upper funnel channels from R&D to production
• Rapidly prototype, test, and iterate on novel marketing strategies in the mid and upper funnel
• Design time- and cost-efficient A/B tests that enable rigorous measurement of the incremental profit impact of marketing campaigns
• Deliver clear and prompt communication of research results that drive action to leaders and stakeholders 
• Build data science pipelines to quickly iterate on research ideas and put them into production
• Take end-to-end ownership of new channels and marketing approaches, continuously improving upon quantitative solutions
• Mentor team members on experimental design, measurement strategy, and data-driven decision making
• Lead planning and prioritization across multiple marketing experiments, ensuring campaign prioritization and scoping are well aligned with strategic goals.

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
• Mid-upper funnel marketing experience:
• • Developing targeted, data-driven marketing strategies and deploying them on DSPs such as The Trade Desk, DV360, or Meta
  • Creating and deploying machine learning targeting models for social, video, display, and/or email campaigns
  • Designing and implementing A/B tests to measure the incremental lift of new campaigns
• Technical skills:
• • Advanced programming skills with experience using modern packages in Python or R; expertise in databases and SQL; familiarity with version control (e.g. Git)
  • Experience with AWS (or analogous) utilities, e.g., EC2, SageMaker, S3, Athena
  • Strong business intelligence and visualization skills, with the ability to speak to many different audiences
• Ownership mentality: takes the initiative to identify, champion, and execute on the highest impact work
• Define the problem: Ability to consider problems from first principles, with the instinct to use expertise and prior experience to guide but not dictate the solution
• Preferred but not required:
• • Experience building and operationalizing media mix models
  • Experience using identity graphs to enhance targeting and measurement of marketing campaigns
  • Insurance industry experience