Principal Marketing Data Scientist

About the Role

Key Responsibilities

• Own TOF measurement & incrementality design, including building an always-on cross-channel measurement architecture covering paid, organic/SEO, owned, influencer/affiliate, brand, and CTV/offline channels.
• Stand up geo/user holdouts, heavy-ups, synthetic controls, CUPED/diff-in-diff, and brand-lift/survey programs to produce trustworthy incremental reach and qualified visit estimates.
• Triangulate MMM, incrementality, and platform MTA with decision rules for budget setting, validation, and operations.
• Forecast, allocate, and de-risk spend by building response curves from media to reach, visits, sign-ups, and LTV with uncertainty bounds.
• Deliver marginal dollar recommendations by channel, geo, and audience, and model payback windows across scenarios.
• Create and ship reporting that drives decisions, including executive-ready views linking leading indicators to outcomes.
• Run always-on traffic-source health monitoring, red-flag alerts, and forward projections to quantify growth costs under uncertainty.
• Unlock audience and creative leverage through analysis of fatigue, hooks, motifs, and documenting lift into playbooks.
• Drive cohort and growth-segment insights to inform media, landing experiences, and lifecycle sequencing.
• Specify and evaluate measurement stack components, prioritize buy-vs-build decisions, and define data quality SLAs.
• Lead through influence by coaching peers, setting standards, and creating reusable documentation.
• Translate ambiguous goals into hypotheses, experiments, and clear trade-off recommendations for senior leaders.

Requirements

• 15+ years in marketing analytics/data science (consumer tech), including principal-level impact and depth in TOF growth.
• Hands-on leadership of incrementality testing (geo/user holdouts, heavy-ups, synthetic controls) and MMM programs.
• Proven experience in budget allocation, response curves, scenario planning, and LTV modeling that influenced investment decisions.
• Advanced SQL and Python or R skills, including pandas/NumPy; Bayesian modeling with PyMC/Stan is a plus.
• Experience with production analytics in BigQuery, Snowflake, or Redshift, with dbt modeling and orchestration tools like Airflow or Dagster.
• Strong storytelling skills using Looker, Tableau, or Mode, with KPI design aligned to business outcomes.
• Practical knowledge of GA4, tag managers, MMPs, ad platforms, CDP, and survey/brand-lift tools.
• Ability to separate seasonality from media effects and turn noisy signals into causally sound recommendations.

Nice to Have

• Linking brand tracking and surveys to search volume and site traffic.
• Measuring brand-to-performance spillovers.
• SEO/ASO opportunity sizing and content decay/refresh modeling.
• Creative-analytics pipelines involving LLM or vision-assisted tagging.
• Experience in international growth, market selection, and localization measurement.
• Experience in education or other high-intent, seasonal categories.

Benefits & Perks

• Total compensation includes a market-competitive starting base salary of $249,000 - $342,000, depending on location and experience, plus stock options.
• Collaborate with your manager and team to create a healthy work-life balance.
• 20 vacation days.
• Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP).
• Employer-sponsored 401k plan with company match.
• Access to LinkedIn Learning and other professional growth resources.
• Paid Family Leave, FSA, HSA, Commuter benefits, Wellness benefits.
• 40 hours of paid time off annually for volunteer programs.