Senior Data Scientist

Join Samba TV as a Senior Data Scientist in Amsterdam. In this role, you will shape the data science function for the future of advertising. You will define modeling methodology, build production ML systems, and apply modern AI capabilities across our data products. You should have 8+ years of experience in machine learning and modern AI, and a strong technical background.

• Define modeling methodology, build production ML systems, and apply modern AI and agentic capabilities across data products.
• Own end-to-end delivery of data science projects, from problem scoping through production deployment, and ensure high standards for production-quality data science.
• Mentor data scientists on the team through structured feedback, pairing, and design review, and establish and operate MLOps practices.
• MLOps proficiency: experiment tracking, pipeline orchestration, model monitoring, reproducible deployment
• Advanced Python with production-quality, tested code; strong SQL and PySpark on billion-row datasets
• An active mentor who invests in others, gives direct feedback, and raises the bar for the team as a whole
• Demonstrated ability to own and deliver complex, multi-sprint data science projects from problem scoping through production deployment
• Production experience with vector databases (Pinecone, Weaviate, Milvus, pgvector, or equivalent) for retrieval, matching, or inference at scale
• Solid command of core ML and statistics, including neural networks, regression, classification, clustering, model evaluation, experimental design, and causal inference, applied to billion-row datasets
• Track record of building methodology, not just applying it: data analysis, model selection, evaluation frameworks, and solid documentation of decision processes
• 8+ years of hands-on data science experience with a Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field (or 6+ years with a Master's, 3+ years with a PhD, or equivalent)
• Experience designing and operating agentic AI systems in production: prompt engineering, agent orchestration, tool use, or integration of LLMs into ML pipelines
• A clear communicator who translates technical work into design docs, user stories, and cross-functional conversations
• Databricks, Delta Lake, and job orchestration (Airflow); hands-on production experience on AWS, GCP, and Databricks
• Knowledge graph design (RDF, OWL, SPARQL, or equivalent graph frameworks), Natural Language Processing, Background in ad tech, CTV/OTT, ACR, audience activation, identity resolution, or measurement methodologies
• Experience with causal inference (A/B testing, synthetic control, uplift modeling)