Data Scientist

Audiohook

Data Scientist at Audiohook responsible for measurement science behind performance audio advertising platform. Collaborating cross-functionally to drive outcomes for advertisers through experiments and modeling.

Posted 6/26/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $120,000 - $170,000 per yearWebsite

Tech Stack

Tools & technologies

BigQueryPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Own the measurement science behind Audiohook's performance audio advertising platform
Design and run incrementality tests, build and maintain marketing mix models, and apply causal analysis to quantify how Audiohook drives outcomes for advertisers
Collaborate closely with Engineering, Product, Sales, and Customer Success to ensure measurement isn't just statistically sound but operationally useful
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

Requirements

What you’ll need

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 (preferred)
Experience with Bayesian methods or Bayesian MMM frameworks (e.g., PyMC-Marketing, LightweightMMM, Robyn) (preferred)
Experience working with large-scale ad event data (impressions, clicks, conversions) and modern data stacks (e.g., Iceberg, Snowflake, BigQuery) (preferred)
Experience in a startup or high-growth company (preferred)
Comfort using AI tools to accelerate exploratory analysis, code, and write-ups while maintaining methodological rigor (preferred)

Benefits

Comp & perks

Fully remote work environment
Competitive salary and equity opportunities
Performance bonuses
Health, dental, and vision benefits
Other benefits such as daily lunch stipend, monthly wifi, cell phone and subscription reimbursement, and 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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data scienceincrementalitymarketing mix modelscausal analysisA/B testingstatistical inferenceregressionBayesian methodsPythonSQL

Soft Skills

communicationattention to detailintellectual honestycollaborationproactive communication