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AI Multivariate Creative Test Designer

Addison Fischer

Full-time · Job · New_York

About the role

A/B testing one creative element at a time is slow. Multivariate testing — testing multiple elements simultaneously (headline, image, call-to-action, color scheme) in combinations — can answer in days what sequential A/B testing takes months to learn. The challenge is experimental design: a full factorial test of 4 elements with 3 variants each requires 81 combinations, which is impractical. Fractional factorial and Plackett-Burman designs test a fraction of combinations while still estimating main effects, but designing these experiments correctly and interpreting the results requires statistical expertise most creative teams don't have. We generate AI creative for 280 brands. Multivariate creative testing is the experimental infrastructure that lets brands learn from generated creative at speed. We have A/B testing integrations. What we don't have is AI-assisted MVT design that generates statistically valid experiment plans from a brand's creative hypotheses, estimates the sample size requirements, and interprets interaction effects once the test data comes in. You'll build the MVT design system: generating experiment plans from creative variable specifications, implementing sample size and power analysis for fractional designs, and building the result interpretation layer that identifies which creative elements drove performance and what interaction effects were observed.

Responsibilities

  • Build MVT experiment plan generator creating fractional factorial designs from brand creative variable specifications
  • Implement sample size and statistical power analysis for proposed experiment designs
  • Develop interaction effect detection identifying which combinations of creative elements drive performance
  • Create result interpretation reports translating MVT statistical outputs into actionable creative direction
  • Build creative hypothesis management allowing brand teams to track and prioritize creative questions
  • Monitor experiment quality flagging underpowered tests or designs with confounded interaction estimates

Requirements

  • 3+ years in marketing analytics, growth engineering, or experimentation with A/B or MVT design experience
  • Strong Python and statistics skills with experimental design, power analysis, and factorial experiment methodology
  • Understanding of creative performance measurement, digital advertising, and brand testing context
  • Experience building tools that make statistical concepts accessible to non-statistician creative teams
  • Ability to explain interaction effects and fractional factorial trade-offs to marketing audiences

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • $2,500 annual professional development budget
  • 401(k) with match
  • Performance bonus

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Categories

AI Business, Marketing & Strategy AI Product & Strategy

Skills

python statistics sql pandas openai api

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

AI Business, Marketing & Strategy AI Product & Strategy

Skills

python statistics sql pandas openai api fastapi

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