As a Junior Data Scientist at Samba in Amsterdam, you will own end-to-end delivery of significant data science projects with minimal guidance. You are a reliable, autonomous contributor with deep expertise in at least one of Samba's core domains — Identity and audience modelling and the technical range to build production-ready solutions using modern ML and AI methodologies. You'll work closely with peers, product, and engineering.
What You'll Do:
Own end-to-end delivery of significant data science projects from problem scoping and approach design through to production deployment
Make sound, independently-reasoned decisions on methodology, model selection, and evaluation; document them clearly in technical solution documents covering problem statement, approach, metrics, and timeline
Lead solution design for your own initiatives; break down complex epics into well-scoped user stories with clear acceptance criteria, adopting DataOps and MLOps best practices throughout — experiment tracking, pipeline orchestration, model monitoring, and reproducibility
Implement advanced ML and AI-powered workflows including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and LLM-augmented pipelines
Develop and maintain reusable tools, libraries, and documentation that improve team efficiency and technical standards; conduct code reviews with constructive, specific feedback that raises the bar
Be a team player and collaborate with different teams.
Collaborate cross-functionally with product, engineering, and operations — translate business requirements into technical specifications, partner with data engineering on scalable pipeline design, and participate in cross-functional design reviews and working groups
Who You Are:
Bachelor's degree required in Statistics, Data Science, Computer Science, Mathematics or a related quantitative field; Master's strongly preferred
2+ years of hands-on data science experience with demonstrated ability to own and deliver complex, multi-sprint projects independently
Advanced Python (or any other programming language+Claude/Codex/any other) with production-quality code, testing, and documentation; strong SQL and PySpark for billion-row datasets
Databricks (nice to have/learn for 2027) workflows, Delta Lake, and job orchestration; working knowledge of cloud platforms (AWS or GCP)
Solid command of core ML — regression, classification, clustering, model evaluation, and experimental design — applied to complex, high-volume data (2 questions to level)
Proficiency with MLOps practices: experiment tracking and reproducible model deployment
Exposure to modern AI methodologies: RAG systems, LLM-augmented models, vector databases, and semantic search (showcase+examples)
Strong communicator — able to translate technical work into clear documentation, user stories, and cross-functional conversations
Demonstrated ability to mentor junior data scientists and contribute to team standards
Team player
Skills Required
- Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field
- 2+ years of hands-on data science experience
- Ability to independently own and deliver complex, multi-sprint data science projects
- Advanced Python or another programming language, with production-quality coding, testing, and documentation
- Strong SQL and PySpark experience for billion-row datasets
- Knowledge of regression, classification, clustering, model evaluation, and experimental design
- Proficiency with MLOps practices, experiment tracking, and reproducible model deployment
- Exposure to RAG systems, LLM-augmented models, vector databases, and semantic search
- Strong written and verbal communication skills
- Ability to mentor junior data scientists and contribute to team standards
- Databricks workflows, Delta Lake, and job orchestration
- Working knowledge of AWS or GCP
- Master's degree in a related quantitative field
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.
