Research Scientist, Marketing Insights and Analytics

About the Role

Key Responsibilities

• Lead Marketing Mix Modeling (MMM) execution and adoption, ensuring methodological rigor and translating outputs into actionable marketing insights.
• Communicate the methodology with data science teams across different orgs, highlighting model advantages and limitations.
• Advocate for MMM's role in budget allocation and campaign optimization.
• Ensure methodological rigor in vendor-led research, reviewing experimental design, statistical approaches, and validity of findings.
• Expand marketing data science capabilities, including: Incrementality Measurement, Budget Optimization, Forecasting & Market Dynamics.
• Build predictive models for scenario planning and strategic marketing investment decisions.
• Influence cross-functional stakeholders (marketing, insights, product, engineering), driving alignment on data-driven marketing strategy.
• Advance causal inference methodologies in marketing measurement, including behavior and conversion lift studies (A/B testing with CUPED & DiD).
• Conduct meta-analyses to assess holistic A/B testing impact and drive strategic recommendations.
• Enhance automation & reporting, maintaining data pipelines, dashboards, and self-serve tools to streamline marketing analytics.

Requirements

• Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
• 5+ years in data science roles within business strategy, marketing, finance, engineering, or analytics organizations.
• Strong programming skills in SQL and either Python or R, with experience in data querying, manipulation, and advanced statistical analysis.
• Experience with experimental design methodologies, including A/B testing and causal inference techniques.
• Proven ability to effectively communicate complex data insights to both technical and non-technical audiences.
• Demonstrated ability to lead complex projects, manage stakeholder relationships, and influence decision-making processes without formal authority.

Nice to Have

• Ph.D. in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
• Strong background in Marketing Mix Modeling (MMM), causal inference (e.g., DiD, Synthetic Control, Instrumental Variables), and experimental design beyond standard A/B testing (e.g., CUPED, meta-analysis, Bayesian methods).
• Experience designing and analyzing geo-testing, creative testing, and incrementality experiments to measure marketing effectiveness and inform budget allocation.
• Proven ability to work with marketing, product, engineering, and operations teams, translating complex statistical insights into actionable business strategies.

Qualifications

• Doctoral degree (preferred, but not required)
• Master's degree in a relevant quantitative discipline

Benefits & Perks

• Paid parental leave
• Paid holidays
• Disability insurance
• Health insurance
• Dental insurance
• RSU (Restricted Stock Units)
• Vision insurance
• 401(k) matching
• Life insurance
• Paid sick time
• Day one access to medical, dental, and vision insurance
• Additional wellbeing benefits
• Paid personal time