Data Scientist

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Audiohook

WebsiteLinkedInAll Job Openings

11 - 50 employees

📱 Media

☁️ SaaS

🤝 B2B

Media • SaaS • B2B

Audiohook is a performance-focused advertising platform specializing in audio and podcast advertising. The company provides programmatic access to premium podcast, streaming, and radio inventory with precise targeting, verified listens, and closed-loop attribution so advertisers can pay for results (CPA/ROAS). Audiohook emphasizes brand safety, privacy-safe measurement, AI-enabled content analysis, and a dashboarded SaaS experience for marketers to plan, launch, and measure audio campaigns.

📋 Description

• 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

• 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

• 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