AdTechTalent
Data Science21 days agoOn-site

Samba TV

Director Data Science, Measurement

causal mlstatistical modelingmeasurement scienceincrementality measurementmulti-touch attributionreach and frequency modelingaudience intelligencepythonsqlpysparkdatabrickssparkab testingdifference-in-differencesbayesian hierarchical modelspanel methodologymachine learningdata scienceleadershipteam managementadvertising measurementdigital measurementtv measurement

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Director

Years experience

10+

Location

San Francisco, United States

Full job description

Samba seeks a Director of Data Science to lead the Measurement science team responsible for statistical frameworks, causal models, and attribution methodologies powering core measurement products. The role involves ownership of incrementality measurement, multi-touch attribution, reach and frequency modeling, and audience intelligence. Responsibilities include defining measurement science strategy with Product, leading technical design and architecture decisions, managing delivery across multiple workstreams, setting scientific standards and data quality with Engineering, implementing best practices for data science lifecycle and MLOps, leading and mentoring a team of data scientists, collaborating cross-functionally, and communicating findings to technical and non-technical stakeholders. Requirements include 8+ years of data science experience with 2-3 years in management, deep expertise in causal ML and measurement science methods, strong Python, SQL, PySpark, and Databricks skills, experience with TV or digital measurement, multi-touch attribution, familiarity with industry vendors and standards, and excellent communication skills. A bachelor's degree in a quantitative field is required; advanced degrees preferred.

What you'll do

  • Partner with Product to define the measurement science roadmap including incrementality, multi-touch attribution, reach/frequency estimation, panel calibration, and audience targeting
  • Lead design reviews and architecture decisions across the team
  • Drive application of Causal ML and broader measurement science methods
  • Own end-to-end delivery of measurement science portfolio managing dependencies and blockers
  • Set and maintain standards for experimental design, model evaluation, reproducibility, and production readiness in partnership with Engineering
  • Develop and implement best practices for data science lifecycle including data management, modeling, evaluation, pipeline orchestration, and production deployment on Databricks/Spark
  • Lead, mentor, and grow a team of data scientists including hiring, performance reviews, career development, and goal-setting
  • Collaborate cross-functionally with Product, Engineering, and Business Development on data-driven measurement projects
  • Support Sales and Marketing with technical positioning and articulation of measurement capabilities
  • Translate complex causal and statistical findings into clear insights for technical and non-technical audiences
  • Represent the team to senior leadership, external stakeholders, and industry forums

Requirements

  • 8+ years of hands-on data science experience with at least 2-3 years in a people management role
  • Demonstrated ability to hire, develop, and retain senior data scientists
  • Deep expertise in Causal ML including counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation
  • Familiarity with EconML, DoWhy, or CausalML is a plus
  • Solid command of measurement science toolkit: A/B testing, difference-in-differences, synthetic control, propensity scoring, Bayesian hierarchical models, panel methodology
  • Strong statistical and ML foundations in regression, classification, experimental design, model evaluation
  • Expert-level Python and SQL; strong PySpark and Databricks experience
  • Track record of delivering complex, multi-workstream data science projects on time
  • Excellent communication skills for technical and non-technical audiences
  • Bachelor's degree in Statistics, Computer Science, Mathematics, or related quantitative field required; Master's or PhD strongly preferred
  • Direct experience with TV or digital measurement including ACR/STB data, viewership panels, reach/frequency modeling, cross-platform measurement
  • Hands-on experience with multi-touch attribution or multi-channel attribution modeling
  • Familiarity with measurement vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC accreditation, GRP/TRP frameworks)
  • Experience with audience segmentation, identity resolution, or privacy-preserving measurement approaches
  • Track record of publishing research, white papers, or presenting at industry conferences

Tech stack

PythonSQLPySparkDatabricksSparkCausal MLEconMLDoWhyCausalMLA/B testingDifference-in-differencesSynthetic controlBayesian hierarchical modelsPanel methodology

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