Top Senior Data Science Jobs in San Diego, CA

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

Design and train LLMs and agentic systems for cybersecurity using RLHF/RLAIF and supervised fine-tuning. Build agent architectures, tooling, retrieval/memory, and evaluation pipelines with rigorous statistical benchmarking. Optimize prompts and inference, collaborate with engineers to productionize prototypes, and drive research on agent planning, safety, and reliability.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Lead development and deployment of predictive models, analytics, and dashboards to support Sales, Marketing, Customer Success, and GTM operations. Mentor data scientists, partner with business leaders to prioritize analytics, ensure data governance and quality, and present insights to executives. Work with Snowflake/data lakes, build scalable ML solutions, and drive analytics adoption across the enterprise.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

Develop, analyze, and deploy data-driven and ML/AI solutions. Perform data analysis, visualization, and decision-support work using Python and version control. Support operational deployments, containerized environments, and cybersecurity considerations; apply NLP/LLM techniques when relevant.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

The Data Scientist II will drive insights, develop models, and analyze product experiments to inform business decisions and improve member experiences in healthcare.

Designs, analyzes, and interprets clinical trial, RWE, and observational data for a medical device. Develops statistical plans, predictive models, and ensures data quality, regulatory compliance, and traceability. Collaborates with clinical, regulatory, and data teams, supports submissions and publications, mentors interns, and represents the company externally.

Lead design and deployment of deep learning and predictive models, mentor data teams, author architecture decisions, collaborate with product and engineering, implement CI/CD and MLOps best practices, and translate ambiguous business problems into high-impact data solutions for multi-unit hospitality customers.

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

The Senior Applied AI Data Scientist will build AI workflows, prototype applications, and enhance decision-support systems while collaborating with various teams to operationalize AI solutions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Senior Marketing Data Scientist, you will conduct quantitative analyses, manage marketing tests, and provide actionable insights to enhance marketing performance and investment effectiveness.

As a Senior Data Scientist, you will lead AI risk assessments, coordinate with stakeholders, and ensure effective AI governance practices for safe financial application deployment.

Senior individual contributor owning complex end-to-end ML problems for supply chain and consumer applications. Build and deploy predictive models (demand forecasting, delivery ETA, recommendations), embed with engineering teams, define MLOps standards, and advise leadership on data science strategy and investments.

As a Staff Data Scientist, you'll design and optimize ML systems for claims handling automation, collaborating with product and engineering teams.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

Embed with a core business unit to define high-impact problems, design metrics and experiments, pull and analyze data, build reports, and drive decisions end-to-end that improve product, growth, AI/automation, or partnerships.

Embedded within a core business area, you’ll define problems, build metrics and analyses, design experiments, surface insights, and drive data-informed decisions end-to-end to move key product, growth, AI, or partnership metrics.