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AI Campaign Budget Allocation Optimizer

Addison Fischer

Full-time · Job · Chicago

About the role

Media mix modeling used to take 6 weeks to run and required a statistician to interpret. Modern approaches can run in hours and surface actionable allocation recommendations — but only if the models are well-calibrated against the actual causal structure of the client's marketing spend, not just the correlational patterns that look compelling in retrospect. We build AI-driven creative and campaign intelligence for 280 B2C brands. Budget allocation optimization is the highest-dollar-value capability on our roadmap: a brand spending $40M per year on media that reallocates even 8% of spend more efficiently gains $3.2M in ROI improvement. Our current allocation recommendations are driven by attribution heuristics. We want causal budget optimization. You'll lead the budget allocation ML capability: implementing Bayesian media mix models that estimate causal channel contribution, building optimization engines that recommend budget shifts under constraints (minimum channel presence, creative lead times, audience saturation), and designing the what-if simulation interface that lets brand managers explore allocation scenarios before committing.

Responsibilities

  • Implement Bayesian media mix models estimating causal channel contribution with uncertainty quantification
  • Build budget optimization engine recommending spend shifts under client-defined constraints
  • Design what-if simulation API supporting scenario exploration for brand manager decision-making
  • Develop saturation curve modeling identifying diminishing returns thresholds per channel
  • Create holdout experiment framework for validating causal estimates against incrementality tests
  • Present optimization recommendations and supporting evidence to client CMOs and media planners

Requirements

  • 6+ years in marketing analytics, media mix modeling, or causal inference for marketing
  • Deep understanding of Bayesian approaches to media mix modeling and marketing attribution
  • Strong Python and statistical modeling skills
  • Experience translating causal model outputs into actionable budget recommendations
  • Track record delivering measurable marketing ROI improvement through data-driven optimization

Benefits

  • Fully remote with flexible schedule
  • Comprehensive health benefits
  • $4,000 annual professional development budget
  • Equity participation
  • Performance bonus tied to client ROI metrics

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Categories

AI Business, Marketing & Strategy data science & analytics

Skills

python pytorch sql pandas statistics

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AI Expertise

AI Business, Marketing & Strategy data science & analytics

Skills

python pytorch sql pandas statistics fastapi

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