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
Similar Jobs
What We Do
Television remains a vibrant cultural influence and an essential source of entertainment and information worldwide. Tremendous growth in content choices, and viewing platforms that allow us to watch anything, anytime, on any screen, has actually made it harder for viewers to discover and keep up with all the great programming available. It’s also more competitive for content providers to keep your attention, and for marketers to make strong, measurable connections with their target consumers. Technology that improves the viewing experience, enables content discovery, and addresses audience fragmentation across screens will strengthen television’s business model and relevance to consumers. Data is at the center of any solution to make TV better. Samba TV's technology is built into Smart TVs and easily maps to smart phones and tablets. By recognizing what's on screen, Samba TV learns what viewers like and using machine learning algorithms, enables discovery of shows and actors in a whole new way. Likewise, our data and measurement products are transforming the way stakeholders across the media landscape are thinking about their business. Given the dramatic growth in streaming services, connected devices, time-shifting, and multi-screen viewership, our data products solve real problems and create a meaningful competitive advantage for our clients.
