Top Data Science Jobs in Santa Cruz, CA

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Design and build custom measurement products by combining Nielsen datasets; develop statistical and ML models; write production-quality SQL, Python, and PySpark; build reusable ETL pipelines; use AI tools and design agentic workflows; translate stakeholder requests, document methodology, and collaborate with Research, Sales, and Insights teams.

Design, build, validate, deploy, and monitor machine learning and generative AI solutions for healthcare and life sciences. Work with EHR, claims, and registry data to produce clinical predictions, operational optimizations, and LLM-powered applications. Translate results for stakeholders, document best practices, and mentor client teams.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Senior individual contributor who builds statistical models and experiments to optimize acquisition, conversion, retention, and lifetime value. Partners with Product, Marketing, and Engineering to define data requirements, analyze A/B tests, perform cohort and funnel analyses, communicate findings to stakeholders, and mentor junior team members while contributing to analytics best practices.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

Lead design and validation of agentic AI capabilities for legal workflows using LLMs, NLP, RAG, hybrid search, embeddings and vector databases. Drive experimentation, evaluation, and metrics, translate results to product recommendations, collaborate with engineers and legal experts, and mentor team members.

Lead end-to-end data science initiatives across pricing, dispatch, ETA, routing, and forecasting. Turn ambiguous logistics problems into production ML solutions, build data pipelines, partner with engineering to deploy models, establish evaluation and A/B testing, and work directly with customers and leadership to measure business impact.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.