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About the Role
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 identity and audience modeling, and the technical range to build production-ready solutions using modern machine learning (ML) and AI methods. You will work closely with peers, product, and engineering.
Responsibilities
- Own end-to-end delivery of significant data science projects, from problem scoping and approach design through to production deployment.
- Make sound, independent decisions on methodology, model selection, and evaluation, and document them in technical solution documents covering problem statement, approach, metrics, and timeline.
- Lead solution design for your own initiatives, breaking epics into well-scoped user stories with clear acceptance criteria and applying DataOps and MLOps practices such as experiment tracking and model monitoring.
- Implement advanced ML and AI-powered workflows, including entity resolution, probabilistic record linkage, embedding-based matching, semantic similarity, and large language model (LLM)-augmented pipelines.
- Develop and maintain reusable tools, libraries, and documentation that raise team efficiency and technical standards, and give constructive, specific code review feedback.
- Collaborate with product, engineering, and operations, translating business requirements into technical specifications, partnering with data engineering on scalable pipeline design, and joining cross-functional design reviews.
Requirements
- Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field, or equivalent practical experience; Master’s strongly preferred.
- 2+ years of hands-on data science experience, with a demonstrated ability to own and deliver complex, multi-sprint projects independently.
- Advanced Python (or another programming language) with production-quality code, testing, and documentation; strong SQL and PySpark for billion-row datasets.
- Databricks workflows, Delta Lake, and job orchestration (nice to have), plus working knowledge of Amazon Web Services (AWS) or Google Cloud Platform (GCP).
- Solid command of core ML (regression, classification, clustering, model evaluation, experimental design) on complex, high-volume data, with MLOps practices including experiment tracking and reproducible model deployment.
- Exposure to modern AI methods: retrieval-augmented generation (RAG) systems, LLM-augmented models, vector databases, and semantic search.
- A strong communicator and team player who turns technical work into clear documentation, user stories, and cross-functional conversations, and who can mentor junior data scientists and contribute to team standards.
Skills
- Identity and audience modeling
- Machine learning (ML)
- AI methods
- Python
- SQL
- PySpark
- Databricks workflows
- Delta Lake
- Job orchestration
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- MLOps practices
- Experiment tracking
- Model monitoring
- Retrieval-augmented generation (RAG) systems
- LLM-augmented models
- Vector databases
- Semantic search
- Communication
- Teamwork
- Mentoring
Experience Level
- 2+ years of hands-on data science experience
Education Level
- Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field, or equivalent practical experience
- Master’s strongly preferred
About the Company
- Samba connects the advertising industry.
- 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.
Equal Opportunity
- Samba is an equal opportunity employer.
- We collect personal information directly from you when you apply. Where the law permits, we may also receive it from third parties, such as through background, employment, or reference checks. For details, see Samba’s Applicant Privacy Policy. For EU residents, Samba Inc. is the data controller.
- We may use AI tools to help review applications, analyze resumes, or assess responses. These tools support our recruiting team. People make every hiring decision. To learn more about how we process your data, please reach out.