Note: The job is a remote job and is open to candidates in USA. Audiohook is a company operating a performance audio advertising platform. The Data Scientist will lead measurement science by designing incrementality experiments, developing marketing mix models, applying causal inference, and translating results into actionable insights for advertisers and internal teams. The role also supports predictive modeling, campaign optimization, and cross-functional product and customer initiatives.
Responsibilities
- Design and run incrementality experiments (geo, ghost bidding, holdout, PSA) that quantify Audiohook's lift for advertisers
- Build, maintain, and evolve marketing mix models (MMM) and multi-touch attribution analyses across customer campaigns
- Apply causal inference methods — difference-in-differences, synthetic controls, instrumental variables, propensity scoring — to questions that can't be answered with RCTs
- Translate measurement results into clear narratives for advertisers, internal stakeholders, and the product team
- Partner with Engineering on the data and modeling layer that powers bidding, pacing, and optimization decisions
- Develop and validate predictive models that improve campaign performance and platform efficiency
- Instrument experiments and analyses for reproducibility, monitoring, and ongoing measurement quality
- Partner with Sales and Customer Success on measurement studies for priority accounts and renewals
- Partner with Product on roadmap inputs grounded in causal evidence, not just descriptive data
- Present findings to advertisers, internal teams, and leadership in clear, decision-ready formats
- Communicate clearly and proactively in a remote-first environment
Skills
- Bachelor's or Master's degree in Statistics, Economics, Data Science, Computer Science, or related quantitative field
- 3–5 years of applied data science experience with a focus on marketing measurement — incrementality, MMM, attribution, or causal analysis
- Hands-on experience designing and analyzing experiments (A/B, geo, holdout) in a marketing or advertising context
- Strong fluency in Python (pandas, statsmodels, scikit-learn, PyMC, or similar) and SQL
- Solid grounding in statistical inference, regression, and causal methods
- Ability to communicate technical results to non-technical audiences — advertisers, sales, leadership
- Excellent attention to detail and intellectual honesty about model limitations
- Experience in adtech, digital advertising, or media measurement
- Experience with Bayesian methods or Bayesian MMM frameworks (e.g., PyMC-Marketing, LightweightMMM, Robyn)
- Experience working with large-scale ad event data (impressions, clicks, conversions) and modern data stacks (e.g., Iceberg, Snowflake, BigQuery)
- Experience in a startup or high-growth company
- Comfort using AI tools to accelerate exploratory analysis, code, and write-ups while maintaining methodological rigor
Benefits
- Fully remote work environment
- Equity opportunities
- Performance bonuses
- Health, dental, and vision benefits
- Daily lunch stipend
- Monthly wifi reimbursement
- Cell phone reimbursement
- Subscription reimbursement
- Annual hardware stipend
- Flexible PTO and remote-friendly culture
- Bi-annual Corporate Offsites
- Opportunity to help shape a function at a rapidly scaling tech company
Company Overview