The Role
Own end-to-end data science projects from scoping through production deployment. Build production-quality Python and PySpark machine learning solutions on Databricks, using entity resolution, record linkage, embeddings, and LLM-augmented pipelines. Apply DataOps and MLOps practices, collaborate with product and engineering, document technical decisions, develop reusable tools, conduct code reviews, and mentor junior data scientists.
Summary Generated by Built In
Samba connects the advertising industry. Today, a trillion dollars of media flows through platforms that don’t talk to each other, and each one measures its own results. We built the independent alternative: consented first-party data and AI that give the world’s biggest advertisers, publishers, and platforms one clear view across all of it.
The next era of advertising will run on AI agents, and those agents will need data they can trust. We’re building that foundation, and the agents that act on it. Join us and help build what the industry runs on.
As a mid-level Data Scientist at Samba in Warsaw, you own end-to-end delivery of significant data science projects with minimal guidance. You bring deep expertise in at least one of Samba's core domains, measurement or audience modeling, plus the technical range to build production-ready solutions with modern ML and AI methods. You work closely with peers, product, and engineering, and mentor junior data scientists on the team.
- Own the Delivery: Own end-to-end delivery of significant data science projects, from problem scoping and approach design through production deployment.
- Decide and Document: Make sound, independently reasoned decisions on methodology, model selection, and evaluation, documenting them clearly for problem statement, approach, metrics, and timeline.
- Design the Solution: Lead solution design for your own initiatives, breaking down complex epics into well-scoped user stories and adopting DataOps and MLOps practices like experiment tracking and pipeline orchestration.
- Build Production ML: Build production-quality Python and PySpark code on Databricks, implementing advanced workflows including entity resolution, probabilistic record linkage, embedding-based matching, and LLM-augmented pipelines.
- Raise the Bar: Develop reusable tools, libraries, and documentation that improve team efficiency, and conduct code reviews with constructive, specific feedback.
- Mentor the Team: Mentor junior data scientists on technical execution, code quality, and career development, and lead internal talks or workshops on machine learning topics.
- Work Cross-Functionally: Translate business requirements into technical specifications, partner with data engineering on scalable pipeline design, and take part in cross-functional design reviews.
What You Bring
- Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field, or equivalent practical experience; a Master's is strongly preferred.
- 3+ years of hands-on data science experience with a demonstrated ability to own and deliver complex, multi-sprint projects independently.
- Advanced Python with production-quality code, testing, and documentation, plus strong SQL and PySpark for billion-row datasets; deduplication or web-to-TV linkage experience is a plus.
- Databricks workflows, Delta Lake, and job orchestration, with cloud platform knowledge (AWS or GCP) and familiarity with knowledge graph or semantic data modeling (RDF, OWL, SPARQL) a plus.
- A solid command of core machine learning, including regression, classification, clustering, and experimental design; causal inference experience (A/B testing, uplift modeling) is a plus.
- MLOps practices such as experiment tracking and pipeline orchestration with Airflow, plus exposure to modern AI methods like retrieval-augmented generation and vector databases.
- A strong communicator who mentors junior data scientists; TV or digital viewership background (ACR, set-top box data) and vendor landscape familiarity (Nielsen, Comscore, LiveRamp) are pluses.
Samba is an equal opportunity employer.
Your personal information
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Use of AI in hiring
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Skills Required
- Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field, or equivalent practical experience
- 3+ years of hands-on data science experience
- Advanced Python, including production-quality code, testing, and documentation
- Strong SQL and PySpark experience with billion-row datasets
- Experience with Databricks workflows, Delta Lake, and job orchestration
- Cloud platform knowledge in AWS or GCP
- Command of core machine learning, including regression, classification, clustering, and experimental design
- MLOps practices, including experiment tracking and pipeline orchestration with Airflow
- Strong communication and mentoring skills
- Master's degree
- Knowledge of entity resolution, deduplication, or web-to-TV linkage
- Knowledge of knowledge graphs or semantic data modeling, including RDF, OWL, or SPARQL
- Causal inference experience, including A/B testing or uplift modeling
- Experience with retrieval-augmented generation and vector databases
- TV or digital viewership background, including ACR or set-top box data
- Familiarity with Nielsen, Comscore, or LiveRamp
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The Company
What We Do
Samba is a media-intelligence company that combines consented first-party viewership data from streaming, linear TV, the web, and video games with AI to map content, audiences, and outcomes. Its platform gives advertisers, publishers, and media platforms insight into audience behavior and supports campaign planning, targeting, measurement, and optimization across channels. Samba’s data and analytics help clients understand audiences and make marketing decisions.
