Salary
💰 $126,000 - $157,500 per year
Tech Stack
AWSEC2PythonSQL
About the role
- Work on Quantitative Science team owning marketing capital allocation and measurement
- Build measurement and experimentation infrastructure for mid- and upper-funnel brand marketing
- Develop causal frameworks, predictive models, and tools linking brand investment to outcomes like quote starts, binds, and lifetime value
- Contribute to brand tracking and survey research and set measurement standards
- Advise stakeholders on interpreting results and allocating spend
- Prototype and test brand strategies, run structured experiments, and optimize targeting, creative, and channel mix
- Build data science pipelines and take end-to-end ownership of new channels and marketing approaches
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 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
- Advanced programming skills in Python or R; expertise in databases and SQL; familiarity with version control (e.g. Git)
- Experience with AWS utilities (e.g., EC2, SageMaker, S3, Athena)
- Strong business intelligence and visualization skills
- Ownership mentality and ability to define problems from first principles
- Preferred: experience with web analytics, customer journeys, identity graphs, or insurance industry experience