Senior Data Scientist: Causal Inference & Growth (Equity)

Atmosphere TV; Austin (TX); Sur place; USD 140 000 - 210 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Company Equity

Company 401(k) with employer matching

Competitive insurance plans

Flexible Time Off Policy

Résumé du poste

Atmosphere TV seeks a Senior Data Scientist to shape our causal inference and predictive-modeling foundation. You will design, build, and ship models measuring campaign impact, venue value, and risk to drive business decisions across sales, product, and GTM.

The role emphasizes applied statistics, rigorous validation, and producing business-facing outputs. You will work in a fast-moving environment to turn data into actionable insights and competitive advantage for Atmosphere.

Responsabilités

• Design and own Atmosphere's causal measurement framework — isolating the incremental impact of exposure on real-world outcomes (foot traffic, store visitation, conversion) from confounders like organic visitation trends, seasonality, and competing media.
• Build statistically rigorous causal designs: exposed/control group construction, geo-based experiments, difference-in-differences, and synthetic control.
• Stand up the incrementality capability that underpins how we sell — turning measurement into a differentiator our go-to-market teams can take to market and our clients can trust.
• Build models that predict a venue's intrinsic revenue potential, enabling us to prioritize prospective venues for acquisition as well as flag under-monetized venues we already operate.
• Leverage venue streaming and engagement data to better understand what drives retention vs. churn, helping us create a ranked list of customer challenges to solve from the full list of potential friction points, pain signals, and leading indicators.
• Model and infer latent venue attributes to sharpen both the segments advertisers target against and the feature sets your own revenue and churn models depend on.
• Use measurement outputs to generate actionable insights that feed back into campaign strategy — daypart targeting, venue type optimization, creative performance, audience segmentation
• Develop closed-loop optimization frameworks that make every campaign smarter than the last, building proprietary benchmarks and norms by vertical/category

Connaissances

Causal inference

Applied statistics

AB testing

Predictive modeling

Python

SQL

Communication

Outils

SQL

Description du poste

Atmosphere TV seeks a Senior Data Scientist to shape our causal inference and predictive-modeling foundation. You will design, build, and ship models measuring campaign impact, venue value, and risk to drive business decisions across sales, product, and GTM.

The role emphasizes applied statistics, rigorous validation, and producing business-facing outputs. You will work in a fast-moving environment to turn data into actionable insights and competitive advantage for Atmosphere.