Senior Data Scientist

AmsterdamEngineering – Product Engineering /International Full Time Employee /HybridSamba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant. 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.What You'll DoModeling and ML DevelopmentOwn 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.AI and Agentic CapabilitiesBuild 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.Technical Contribution and CollaborationDrive 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.MLOps and Production PracticeEstablish 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.Who You AreRequired8+ 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).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.Track record of building methodology, not just applying it: data analysis, model selection, evaluation frameworks, and solid documentation of decision processesProduction 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.Databricks, Delta Lake, and job orchestration (Airflow); hands-on production experience on AWS, GCP, and Databricks.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.A clear communicator who translates technical work into design docs, user stories, and cross-functional conversations.An active mentor who invests in others, gives direct feedback, and raises the bar for the team as a whole.PreferredKnowledge 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).Base salary is just one component of Samba total compensation package for employees. Other rewards may include bonuses, short-term incentives, and long-term incentives. In addition, Samba provides health insurance, wellness offerings, life and disability insurance, a retirement savings plan, paid holidays and paid time off (PTO), and other employee benefits.Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.