Senior Marketing Decision Scientist II

Instacart Instacart · Consumer · United States · Remote · Analytics

Instacart is seeking a Senior Marketing Decision Scientist II to join their Marketing Data Science and Analytics team. This role will focus on measuring, forecasting, and optimizing marketing performance across various channels, informing investment decisions and driving customer acquisition and retention. The position involves owning end-to-end measurement strategy, designing and analyzing experiments, building predictive models, creating dashboards, and partnering with finance and marketing leadership. The ideal candidate has extensive experience in marketing analytics, SQL, Python/R, experimental design, causal inference, and dashboarding tools.

What you'd actually do

  1. Own the end-to-end marketing measurement strategy across paid search, paid social, display, affiliates, CTV, and lifecycle/CRM, unifying MMM, MTA, and incrementality testing to guide channel and portfolio-level investment.
  2. Design, launch, and analyze experiments (e.g., geo tests, PSA tests, holdouts) and causal inference studies that quantify lift, inform targeting, and establish best practices for decision-making under uncertainty.
  3. Build and productionize predictive models (e.g., LTV, churn/propensity, audience response, budget allocation) using SQL and Python or R, partnering with data engineering to automate pipelines and ensure data quality.
  4. Create executive-ready dashboards and narratives in tools like Looker or Mode that track KPIs, explain performance drivers, and translate insights into clear, prioritized recommendations.
  5. Partner with Strategic Finance and Marketing leadership on forecasting, scenario planning, and quarterly planning processes; influence roadmaps and present findings to VP+ stakeholders.

Skills

Required

  • 6+ years of experience in marketing analytics or data science
  • Advanced proficiency in SQL
  • Proficiency in Python or R for data manipulation, statistical analysis, and modeling
  • Hands-on experience designing and analyzing marketing experiments (e.g., A/B tests, geo experiments, holdouts)
  • Experience applying causal inference techniques to estimate incrementality
  • Proven track record implementing at least one marketing measurement approach (e.g., MMM, MTA, or structured incrementality testing)
  • Experience building business-facing dashboards and self-serve tools in Looker, Tableau, or Mode
  • Experience working with modern data warehouses (e.g., Snowflake, BigQuery, or Redshift)
  • Experience with version control (Git)
  • Demonstrated ability to translate ambiguous business questions into analytical roadmaps
  • Ability to communicate clear, actionable recommendations to non-technical and executive audiences
  • Bachelor’s degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Mathematics, Engineering) or equivalent practical experience

Nice to have

  • 8+ years of relevant experience
  • Advanced degree (MS/PhD) in a quantitative discipline
  • Experience building, validating, and operationalizing Marketing Mix Models (preferably Bayesian approaches using PyMC, Stan, or similar)
  • Experience triangulating MMM with experiment results
  • Familiarity with privacy-conscious measurement (e.g., conversion modeling, SKAN, clean rooms such as Amazon Marketing Cloud or Ads Data Hub)
  • Familiarity with ad platform APIs
  • Experience with analytics engineering and pipeline tooling (e.g., dbt, Airflow)
  • Strong data QA practices
  • Background in lifecycle/CRM analytics (e.g., uplift modeling, audience selection, message experimentation)
  • Experience with LTV forecasting
  • Exposure to experimentation platforms and feature flagging (e.g., Optimizely or internal frameworks)
  • Exposure to ML applications for bidding, pacing, and creative optimization
  • Experience mentoring peers
  • Experience elevating analytical standards through code reviews, reproducible research, and documentation

What the JD emphasized

  • Own the end-to-end marketing measurement strategy
  • Design, launch, and analyze experiments
  • Build and productionize predictive models
  • Create executive-ready dashboards and narratives
  • Partner with Strategic Finance and Marketing leadership
  • Prioritize ruthlessly
  • Advanced proficiency in SQL and in either Python or R
  • Hands-on experience designing and analyzing marketing experiments
  • Proven track record implementing at least one marketing measurement approach
  • Experience building business-facing dashboards and self-serve tools
  • Experience working with modern data warehouses
  • Demonstrated ability to translate ambiguous business questions into analytical roadmaps