Senior Data Scientist

Salary Range: 160000 to 220000 (Currency: USD) (Pay period: per-year-salary)

What You'll Do

• Design and implement ad incrementality measurement methodologies (A/B tests, uplift modeling, synthetic controls, Bayesian causal models) for linear TV and Connected TV (CTV) campaigns  
• Develop globally scalable audience segmentation and targeting models using our viewership data ecosystem via millions of connected TVs
• Build and validate multi-touch attribution frameworks that reconcile impressions, views, and conversions across linear, CTV, OTT, and digital channels  
• Lead the full analytics lifecycle—from data ingestion/ETL (SQL, Spark, Python) through feature engineering, model development, evaluation, and production deployment  
• Partner closely with data engineering and DevOps teams to operationalize models in our cloud platform and ensure data quality, security, and scalability  
• Translate complex analytical findings into clear, concise presentations and dashboards for internal stakeholders and external clients, driving strategic decision-making. 
• Support sales and marketing teams with the development of strong positioning stories to highlight the value of our audience media and measurement opportunities
• Mentor junior data scientists and analytics engineers, fostering best practices in experimentation, code quality, and reproducibility  

Who You Are

• Have a Master’s or advanced degree in Statistics, Econometrics, Data Science, Computer Science, or related quantitative field  
• 7-10 years of hands-on experience in advertising/marketing analytics, media measurement, or a closely related discipline  
• Expert in causal inference techniques (RCT design, difference-in-differences, propensity scoring, synthetic control) and uplift modeling. Background in Bayesian statistics or hierarchical modeling for uncertainty quantification  
• Have a proven track record building attribution and incrementality solutions for TV and cross-media campaigns  
• Have advanced programming skills in Python and SQL; Familiarity with Spark or other distributed compute frameworks  
• Have demonstrated leadership in mentoring small data science teams and managing end-to-end data science projects
• Able to visualize data in a way that makes it easy for others to understand
• Are detail-oriented, highly organized, and proactive
• Have strong verbal and written communication skills, with the ability to explain complex analyses to both technical and non-technical audiences  
• Thrive in a dynamic, fast-paced Agile and global environment, and being a team player
• Experience with data platforms (Databricks, Sagemaker, BigQuery, etc.), data orchestration tools (Airflow, dbt) and CI/CD best practices a plus
• Bonus: Strong knowledge or experience working with TV viewership data sources (set-top box, return-path, panel, census-level) and measurement vendors (Samba TV, Nielsen, Comscore, etc.)
• Bonus: Track record of publishing research and white papers or presenting at industry conferences




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