Senior Data Scientist

• We are hiring a Senior Data Scientist in Amsterdam to help shape Samba TV’s data science function for the agentic era of advertising
• You will define modeling methodology, build production ML systems, and apply modern AI and agentic capabilities across our data products
• You bring 8+ years of experience, deep expertise in machine learning and modern AI, and the technical range to take methodology from research through production deployment
• You are an active collaborator with engineering, product, and partner teams, and an advocate for rigorous, defensible modeling practice
• Own end-to-end delivery of data science projects, from problem scoping through production deployment
• Define and ship modeling methodology that powers Samba’s data products, including model selection, evaluation frameworks, and reproducibility standards
• Apply solid command of core ML and statistics (regression, classification, clustering, model evaluation, experimental design, causal inference) to billion-row, real-world data
• Build production-quality Python and PySpark on Databricks: well-tested, documented, reusable
• Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable and production-ready
• Build and operate advanced AI systems using modern methodologies: retrieval-augmented generation (RAG), LLM-augmented modeling and Graph Neural Networks. Design AI-driven modeling approaches that improve as signals evolve, supporting agentic decision-making at platform scale
• Integrate LLMs and agentic workflows into production ML pipelines where they extend modeling capability and unlock new product surfaces
• Drive technical design for modeling components within your scope, producing clear solution documents covering problem statement, approach, metrics, and trade-offs
• Translate business requirements into modeling solutions in close collaboration with product, engineering, and go-to-market partners
• Uphold high standards for production-quality data science
• Mentor data scientists on the team through structured feedback, pairing, and design review
• Establish and operate MLOps practices: experiment tracking, pipeline orchestration (Airflow), model monitoring, retraining workflows, and reproducibility standards
• Apply privacy-compliant data handling practices, including GDPR, CCPA, and Samba’s data governance policies

Benefits

• Health Coverage: We have several choices of medical, dental, and vision plans with a range of coverage levels and costs, including a 100% employer-covered plan.
• Wellness & Lifestyle Perks: Our wellness programs are designed to help you maintain or move toward a healthy lifestyle through mindful meditations, gym access, and other assistance when you need it!
• Company Equity Plan: We believe in shared success. We want our employees to not just work for us, but to truly be part of our growth story.
• Volunteer Days: We’re committed to making a positive impact, both in and outside the workplace!
• Flexible Time Off: We encourage a healthy work-life balance which empowers our teams to recharge when needed and thrive both personally and professionally.
• Team & Company Events: We love to hang out together! We provide many opportunities to get to know each other whether virtually or in person.

• Demonstrated ability to own and deliver complex, multi-sprint data science projects from problem scoping through production deployment
• 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
• MLOps proficiency: experiment tracking, pipeline orchestration, model monitoring, reproducible deployment
• Experience designing and operating agentic AI systems in production: prompt engineering, agent orchestration, tool use, or integration of LLMs into ML pipelines
• Production experience with vector databases (Pinecone, Weaviate, Milvus, pgvector, or equivalent) for retrieval, matching, or inference at scale
• Advanced Python with production-quality, tested code; strong SQL and PySpark on billion-row datasets
• 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)
• Databricks, Delta Lake, and job orchestration (Airflow); hands-on production experience on AWS, GCP, and Databricks
• An active mentor who invests in others, gives direct feedback, and raises the bar for the team as a whole
• Track record of building methodology, not just applying it: data analysis, model selection, evaluation frameworks, and solid documentation of decision processes
• A clear communicator who translates technical work into design docs, user stories, and cross-functional conversations
• 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)