Senior Data Scientist, Brand Marketing

Root Insurance

104d • $126,000 - $157,500 • Remote

About The Position

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 Senior Data Scientist on the Marketing team, you’ll help deepen Root’s brand presence by building the measurement and experimentation infrastructure needed to grow our mid- and upper-funnel marketing. You’ll develop causal frameworks, predictive models, and tools to link brand investment to business outcomes like quote starts, binds, and lifetime value. This role is R&D-heavy, focused on high-uncertainty problems with delayed feedback loops. You’ll also contribute to brand tracking and survey research, help set measurement standards, and advise stakeholders on interpreting results and allocating spend.

Requirements

• Advanced degree in a quantitative discipline (PhD preferred) and 4+ years of applying advanced quantitative techniques to problems in industry
• Quantitative brand marketing experience:
• Experience measuring brand impact in mid- and upper-funnel channels using causal inference methods (e.g., synthetic control, Bayesian models, geo-testing
• Skilled in designing and analyzing brand lift studies and survey-based measurement
• Developed data-driven brand strategies and deployed them through DSPs like The Trade Desk, DV360, or Meta
• Built and applied ML models to improve targeting for brand-focused campaigns across social, video, and display
• Designed and implemented experiments to quantify the incremental effect of brand exposure on downstream metrics
• 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

Nice To Haves

• Experience with web analytics, customer journeys, measuring early engagement
• Experience using identity graphs to enhance targeting and measurement of marketing campaigns
• Insurance industry experience

Responsibilities

• Design measurement frameworks that quantify the impact of brand marketing in mid- and upper-funnel channels, separating signal from noise over long time horizons
• Prototype and test brand strategies using structured experiments, focusing on downstream outcomes like engagement, quote starts, and lifetime value
• Improve the efficiency of brand generation by optimizing targeting, creative, and channel mix through data-driven experimentation and modeling
• Translate research findings into clear, actionable insights that inform brand strategy and investment decisions
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 11-50 employees