Data Science Manager at Sambatv

Samba TV is a global leader in tracking streaming and broadcast video through proprietary technology, and we are on a mission to transform the viewing experience for audiences everywhere. We are looking for a Data Science Manager to join our Warsaw office and lead a team that turns complex data into actionable insights for media companies and advertisers.

Responsibilities

• Lead, mentor, and grow a team of 6 to 8 data scientists by overseeing hiring, performance reviews, and career development.
• Direct the research and technology roadmap for TV viewership measurement, audience segmentation, and panel weighting.
• Partner with engineering teams to productionize scalable data pipelines using tools like Spark, Airflow, Databricks, and BigQuery.
• Promote technical excellence by championing best practices such as code reviews, modular architectures, and thorough documentation.
• Communicate strategic findings and recommendations to senior leadership and key external stakeholders.
• Foster a collaborative, high-performance culture that prioritizes continuous learning and growth.
• Work closely with global product, sales, and analytics departments to ensure our deliverables meet client needs.
• Contribute hands-on to model development, including predictive, causal, and hierarchical models for attribution and panel calibration.

Must-haves

• Master’s or advanced degree in Statistics, Computer Science, Mathematics, or a related quantitative field.
• At least 7 years of hands-on data science experience, with at least 2 years in a people-management or team-lead role.
• Proven ability to lead data science teams and manage end-to-end projects.
• Strong programming proficiency in Python and SQL, along with familiarity with Spark or other distributed computing frameworks.
• Experience working with cloud platforms like GCP, AWS, and Databricks.
• Practical knowledge of MLOps tools, including Docker, Airflow, and CI/CD pipelines.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences.
• Ability to balance long-term strategic vision with tactical execution in a fast-paced, Agile environment.
• Fluency in English.

Nice-to-haves

• Expertise in causal inference methodologies, such as uplift modeling, synthetic control, A/B testing, and Bayesian statistics.
• Background in multi-touch attribution across linear and CTV/OTT channels.
• Strong knowledge of TV viewership data, including ACR and STB data, panel weighting techniques, and census-level data.
• Familiarity with measurement vendors like Nielsen or Comscore.

Benefits

• Hybrid work model.