Top Data Science Jobs in San Diego, CA

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.

Partner with pricing and product teams to develop, implement, and maintain pricing and demand models. Lead predictive modeling, optimization, back-testing, and performance monitoring. Translate business problems into analytical solutions, collaborate with Finance on forecasting and profitability, and communicate findings to stakeholders while ensuring model governance and production readiness.

As a Principal Data Scientist, you'll drive data-driven strategies across Growth and Membership Operations, integrating AI tools and managing complex data systems to enhance operational performance.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

The Applied Data Scientist will manage client engagements, unifying datasets, building models, deriving insights, and collaborating with teams to implement solutions.

The Data Scientist will develop and improve models and LLM systems for security applications, focusing on production readiness and experimentation. Responsibilities include building classifiers and evaluating models.

The Data Scientist I will analyze large datasets, build predictive models, conduct A/B testing, and communicate insights to stakeholders, enhancing business solutions.

The Principal Data Scientist Consultant will develop and maintain clinical datasets using R, ensure CDISC compliance, generate reports, and contribute to internal tools while collaborating with clinical teams.