What You'll Do
- Lead, mentor, and develop a team of 4–6 data scientists, owning performance reviews, career development, goal-setting, and promotion readiness aligned to Samba's leveling framework
- Define meaningful KPIs for each team member; hold regular 1:1s to track progress, surface blockers, and support growth
- Drive hiring, onboarding, and a high-engagement team culture grounded in psychological safety, continuous learning, and accountability
- Partner with product, engineering, and analytics to align priorities and translate the team's roadmap into well-scoped quarterly plans and sprint commitments
- Own delivery execution — sprint planning, backlog grooming, dependency management, and blocker removal — and communicate progress, risks, and blockers clearly to senior leadership
- Participate actively in technical scoping and solution design across data science initiatives, with a focus on knowledge graph, entity resolution, and identity-linked audience modeling
- Champion best practices across teams — code reviews, modular architectures, documentation — foster knowledge-sharing, and jump in hands-on on high-complexity work as needed
Who You Are
- Bachelor's degree required in Statistics, Data Science, Computer Science, Mathematics or related field; Master's preferred
- 5-7 years of hands-on data science experience with 1-2+ years in a direct people-management or team-lead role with demonstrated ability to develop, retain, and hire data scientists
- Solid command of core statistics and ML - hypothesis testing, probability, regression, classification, clustering, model evaluation, and experimental design
- Strong Python (pandas, NumPy, PySpark, scikit-learn) and SQL; Databricks or similar platform experience essential
- Familiarity with MLOps practices: experiment tracking, pipeline orchestration (Airflow), reproducible model deployment
- Detail-oriented and proactive in anticipating delivery risks
- Comfortable running Agile ceremonies and maintaining consistent sprint cadence across a distributed team
- Strong communicator - able to give direct, constructive feedback and advocate for your team to key stakeholders
- Hands-on experience with knowledge graph construction, ontology design, or semantic data modeling (RDF, OWL, SPARQL, or equivalent graph frameworks)
- Familiarity with entity resolution, probabilistic record linkage, or identity graph approaches at scale
- Experience applying graph-based or embedding-based methods to real-world entity matching, deduplication, or enrichment problems
- Exposure to modern AI methodologies: RAG pipelines, embedding models, vector search, and LLM-based approaches
- Background in media, ad tech, or measurement — TV viewership (ACR/STB data), digital audience modeling, cross-platform measurement (linear + CTV/OTT), or identity resolution in privacy-constrained environments
- Familiarity with the measurement and identity vendor landscape (Nielsen, Comscore, LiveRamp, The Trade Desk) a plus
- Experience with causal inference (A/B testing, synthetic control, uplift modeling) a plus
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.
