Senior Data Scientist

Modeling and ML Development

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.

AI and Agentic Capabilities

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.

Technical Contribution and Collaboration

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.

MLOps and Production Practice

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.