Data Scientist

5-7 years of professional data science experience — hands-on, delivery-focused, and measurable in shipped models and production systems

Expert-level Python — clean, modular, testable, production-ready code is your standard, not your aspiration

Advanced PySpark and Databricks — comfortable building and optimizing data pipelines and ML workflows on billion-row datasets

Deep, first-principles command of statistics and ML — you can explain from the ground up how these models work and you apply this understanding to make better modeling decisions

Solid grasp of experimental design — A/B testing, randomization, power analysis, and the conditions under which observational causal inference is appropriate

Fluent in the full ML lifecycle: feature engineering, model evaluation, deployment pipelines, drift monitoring, and iterative improvement in production

Hands-on experience with uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches applied to advertising or media outcomes

Strong ownership mindset — you drive projects independently and are comfortable owning your models from data exploration through production delivery, with minimal hand-holding.

Clear communicator — able to translate statistical reasoning and model behavior into language that drives decisions with product, engineering, and leadership

Experience with multi-touch attribution (MTA) or multi-channel attribution modeling — understanding of the limitations of rule-based approaches and the methodological trade-offs of data-driven alternatives

Hands-on experience with Causal ML methods — counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation — applied to advertising or media measurement outcomes

Direct exposure to TV or digital viewership data — ACR signals, STB data, viewership panels, or cross-platform measurement (linear + CTV/OTT)

Familiarity with the measurement

t vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC, GRP/TRP frameworks)

Advanced degree (MS or PhD) in Statistics, Mathematics, Computer Science, or a related quantitative field — or equivalent depth demonstrated through work