Data Scientist
Audiohook · Remote · United States ·
COMPENSATION
$120k – $170k
Listed on the employer's job board (Ashby)
- Fully remote
- 3–5 years experience
- Python + SQL
- Causal inference focus
- Adtech industry
You will own the measurement framework behind Audiohook’s audio advertising platform, designing incrementality tests and building marketing mix models. Your work will apply causal analysis to demonstrate how the platform drives outcomes for advertisers, combining hands-on modeling with strategic influence on product direction.
Collaboration is central to this role, as you will partner with Engineering to refine bidding systems and work with Sales and Customer Success to provide measurement insights for key accounts. You will translate complex statistical results into clear narratives for both technical and non-technical stakeholders.
What you'll do
- Design and execute incrementality experiments such as geo tests, ghost bidding, and holdouts
- Build and maintain marketing mix models and multi-touch attribution analyses
- Apply causal inference methods like difference-in-differences and synthetic controls
- Partner with Engineering to improve data layers for bidding and optimization
- Develop predictive models to enhance campaign performance and platform efficiency
- Present measurement findings to advertisers, internal teams, and leadership
What you'll need
- Bachelor's or Master's in Statistics, Economics, Data Science, or related field
- 3–5 years of applied data science experience in marketing measurement
- Hands-on experience designing A/B, geo, or holdout experiments
- Strong proficiency in Python libraries such as pandas, statsmodels, and scikit-learn
- Solid understanding of statistical inference, regression, and causal methods
- Ability to communicate technical results to non-technical audiences clearly
Nice to have
- Experience in adtech, digital advertising, or media measurement
- Familiarity with Bayesian methods or frameworks like PyMC-Marketing
- Experience with large-scale ad event data and modern data stacks
- Background in startup or high-growth company environments
- Comfort using AI tools for exploratory analysis and coding
Stack
- Python
- SQL
- pandas
- statsmodels
- scikit-learn
- PyMC
- Snowflake
- BigQuery
How you'll work
- Fully remote work environment
- Remote-first culture with flexible PTO
- Bi-annual corporate offsites
What you get
- Competitive salary and equity opportunities
- Performance bonuses
- Health, dental, and vision benefits
- Daily lunch stipend
- Monthly wifi, cell phone, and subscription reimbursement
- Annual hardware stipend