Jobs and Careers

Director Data Science, Measurement

San Francisco, United Statesfull_timeVerifiedPosted 10 Jul 2026

About the role

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.

Reporting to our VP of Data Science, Samba is looking for a Director of Data Science to lead our Measurement science team - the group responsible for building the statistical frameworks, causal models, and attribution methodologies that power Samba's core measurement products. You will own the science and delivery for a portfolio spanning incrementality measurement, multi-touch attribution, reach and frequency modeling, and audience intelligence, working closely with Product to shape direction and with Engineering to bring solutions to production.

You are a senior technical leader first. You bring deep, hands-on expertise in causal ML, statistical modeling, and measurement science - enough to drive architectural decisions, mentor senior data scientists, and engage credibly in design reviews. You also know how to build and run a high-performing team, communicate clearly to executive and external audiences, and keep complex multi-workstream delivery on track.

WHAT YOU'LL DO

Measurement Science Strategy: Partner with Product to define the measurement science roadmap - spanning incrementality, multi-touch attribution, reach/frequency estimation, panel calibration, and audience targeting. Translate business and client priorities into well-scoped quarterly plans and sprint commitments.
Technical Leadership: Lead design reviews and architecture decisions across the team. Drive the application of Causal ML - counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation - as the primary framework for measuring ad effectiveness, alongside rigorous command of the broader toolkit: A/B testing, DiD, synthetic control, Bayesian hierarchical models, and panel methodology.
Delivery & Execution: Own end-to-end delivery across the team's measurement science portfolio - managing dependencies, removing blockers, and ensuring timely delivery of high-quality work across multiple concurrent workstreams.
Scientific Standards & Data Quality: In partnership with Engineering, set and maintain standards for experimental design, model evaluation, reproducibility, and production readiness. Co-own the data quality framework that ensures the robustness and consistency of measurement products used by clients and internal stakeholders.
Best Practices & MLOps: In partnership with Engineering, develop and implement best practices for the full DS lifecycle - data management, modeling, evaluation, pipeline orchestration, and production deployment on Databricks/Spark.
People & Team Leadership: Lead, mentor, and grow a team of data scientists - owning hiring, performance reviews, career development, and individual goal-setting aligned to Samba's leveling framework. Build a high-accountability culture grounded in technical rigor, psychological safety, and continuous learning.
Cross-functional Partnership: Collaborate with Product, Engineering, and Business Development to define and execute data-driven measurement projects. Support Sales and Marketing with technical positioning and clear articulation of Samba's measurement capabilities.
Stakeholder Communication: Translate complex causal and statistical findings into clear, actionable insights for technical and non-technical audiences. Represent the team to senior leadership and external stakeholders, and contribute a credible technical voice to client conversations and industry forums.

WHO YOU ARE

8+ years of hands-on data science experience with at least 2-3 years in a people management role, including demonstrated ability to hire, develop, and retain senior data scientists
Deep, first-principles expertise in Causal ML - counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation - applied to advertising measurement or media outcomes; familiarity with EconML, DoWhy, or CausalML a plus
Soli