Senior Data Scientist

Modeling and ML Development

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  Own end-to-end delivery of data science projects, from problem scoping through production deployment.

  
  


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  Define and ship modeling methodology that powers Samba's data products, including model selection, evaluation frameworks, and reproducibility standards.

  
  


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  Apply solid command of core ML and statistics (regression, classification, clustering, model evaluation, experimental design, causal inference) to billion-row, real-world data.

  
  


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  Build production-quality Python and PySpark on Databricks: well-tested, documented, reusable.

  
  


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  Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable and production-ready.

  
  

AI and Agentic Capabilities

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  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.

  
  


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  Integrate LLMs and agentic workflows into production ML pipelines where they extend modeling capability and unlock new product surfaces.

  
  

Technical Contribution and Collaboration

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  Drive technical design for modeling components within your scope, producing clear solution documents covering problem statement, approach, metrics, and trade-offs.

  
  


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  Translate business requirements into modeling solutions in close collaboration with product, engineering, and go-to-market partners.

  
  


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  Uphold high standards for production-quality data science.

  
  


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  Mentor data scientists on the team through structured feedback, pairing, and design review.

  
  

MLOps and Production Practice

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  Establish and operate MLOps practices: experiment tracking, pipeline orchestration (Airflow), model monitoring, retraining workflows, and reproducibility standards.

  
  


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  Apply privacy-compliant data handling practices, including GDPR, CCPA, and Samba's data governance policies.

  
  

Required

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  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).

  
  


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  Demonstrated ability to own and deliver complex, multi-sprint data science projects from problem scoping through production deployment.

  
  


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  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.

  
  


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  Track record of building methodology, not just applying it: data analysis, model selection, evaluation frameworks, and solid documentation of decision processes

  
  


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  Production experience with vector databases (Pinecone, Weaviate, Milvus, pgvector, or equivalent) for retrieval, matching, or inference at scale.

  
  


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  Advanced Python with production-quality, tested code; strong SQL and PySpark on billion-row datasets.

  
  


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  Databricks, Delta Lake, and job orchestration (Airflow); hands-on production experience on AWS, GCP, and Databricks.

  
  


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  MLOps proficiency: experiment tracking, pipeline orchestration, model monitoring, reproducible deployment.

  
  


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  Experience designing and operating agentic AI systems in production: prompt engineering, agent orchestration, tool use, or integration of LLMs into ML pipelines.

  
  


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  A clear communicator who translates technical work into design docs, user stories, and cross-functional conversations.

  
  


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  An active mentor who invests in others, gives direct feedback, and raises the bar for the team as a whole.

  
  

Preferred

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  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.

  
  


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  Experience with causal inference (A/B testing, synthetic control, uplift modeling).