Top Data Science Jobs in San Diego, CA

As Staff Data Scientist, you will drive advanced analytics to optimize sales performance, build predictive models, and develop insights for decision-making across the GTM organization.

Lead data science efforts for the Rentals Shopping pillar, driving strategy, modeling, experimentation, and cross-functional collaboration to improve user experience and business performance.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end data science projects: develop and productionize models, build segmentation and performance models, run experiments/causal analyses, deliver insights to stakeholders, and mentor junior team members while contributing to scalable data assets and cross-functional collaboration.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

Join as a Data Scientist II to develop AI systems for biomedical research, focusing on LLMs and computer vision, while collaborating with researchers.

Develop a tool to enhance signature management capabilities and integrate diverse data holdings, leveraging AI/ML solutions to meet operational needs.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

Lead development and evolution of forecasting assets using statistical, ML, and AI-driven methods. Own model development, feature engineering, EDA, ensemble and hierarchical forecasting, and evaluation. Integrate foundation models and deep learning where beneficial, collaborate with stakeholders to drive measurable impact, and support deployment and operationalization of forecasting solutions within a shared Center of Excellence.

Lead design, development, and deployment of end-to-end recommendation systems. Build, tune, and evaluate scalable recommendation algorithms, integrate ML into products, lead projects, mentor teams, and communicate solutions to clients and stakeholders while driving innovation in replenishment and supply chain analytics.

As a Senior Data Scientist, analyze healthcare data to improve health outcomes, develop reports and dashboards, and collaborate across teams to leverage genomic data for health insights.

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

Design and validate clinical and biomarker data pipelines, perform source-to-target mappings (e.g., EHR to data model), extend ontologies and vocabularies, ensure data quality, evaluate informatics tools, and support data architecture and analysis workflows for a regulatory-grade platform.

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

The Data Scientist II will analyze data, create actionable insights, develop algorithms, and support the go-to-market team to drive revenue while educating customers on the value of Socure's products.

The Data Scientist II role involves developing scalable analysis frameworks, building monitoring systems, enhancing data pipelines, and facilitating model improvements for customer success while collaborating across teams.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.

Develop, validate, and implement econometric and predictive credit risk models. Extract, clean, and analyze large datasets from relational and datalake sources. Monitor, backtest, and troubleshoot model performance, ensure adherence to credit policy, collaborate with business partners, document models, and support deployment including third-party vendor solutions.