Top Data Science Jobs in Richmond, VA

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

As a Senior Data Scientist, you'll partner with marketing stakeholders to develop analytical models, generate insights, and improve business decision-making through data-driven recommendations.

The Data Scientist will drive product innovation at Netflix by applying analytics, modeling, and experimentation to enhance the member experience for mobile users and content discovery.

The Forward-Deployed Data Scientist will validate healthcare data quality, analyze and visualize data using SQL and Python, and collaborate with clients and internal teams to enhance AI models and customer delivery processes.

The Staff Data Scientist will enhance engagement strategies using machine learning, lead cross-functional projects, mentor junior scientists, and collaborate on product insights.

As a Staff Marketing Data Scientist, you will develop innovative measurement methodologies, lead analytics frameworks, and collaborate to drive data-informed marketing strategies.

As a Data Scientist, you will analyze large datasets, translate client goals into analytical solutions, and communicate findings effectively. You'll collaborate with teams to improve analytics processes and ensure data quality.

The Senior Responsible AI Data Scientist will lead ethical AI initiatives, ensuring compliance and transparency while working cross-functionally to develop scalable AI solutions in healthcare.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

Analyze and interpret complex data sets, develop predictive models, collaborate with teams, create visualizations, and communicate insights.

The Staff Data Scientist will provide quantitative support and strategic insights, utilize technical expertise for data analysis, and collaborate with cross-functional teams to enhance product strategies and performance.

As a Staff Data Scientist in AI Products, you will drive AI/ML capabilities, influence product strategy, and collaborate with various teams to enhance data foundations.

As a Data Scientist, you will model healthcare data, build pipelines, and collaborate with teams to enhance patient care analytics and reporting.

As a Data Scientist, you'll develop statistical models, analyze data, build data pipelines, and collaborate to provide data-driven insights.

As a Staff Data Scientist, you will enhance Mozilla's operational efficiency by creating reporting systems, automating workflows, employing AI tools, and collaborating on metrics and performance analysis.

This role involves building credit risk models, bridging data science with MLOps, ensuring model reliability, and supporting compliance tasks.

The Staff Data Scientist supports marketing intelligence products by enhancing forecasting and experimentation models, translating customer needs into technical requirements, and troubleshooting measurement issues.

The Data Scientist will perform research on DeFi protocols, manage client engagements, and create dashboards while analyzing complex datasets.

Design and develop AI-driven tools for meta-analysis and RWE generation, collaborating with teams to ensure scientific rigor and compliance. Leverage LLMs and MLOps best practices while mentoring team members and driving innovation in healthcare analytics.

Collaborate with data scientists to build models for recommendations and user segmentation, design A/B tests, and deploy ML models while ensuring clean, maintainable code.

As a Data Scientist II, you will develop and deploy machine learning models, monitor performance, and communicate findings across teams. Collaboration and ownership of ML products are key.

The Staff Data Scientist will design and optimize AI-driven machine learning models for healthcare applications, ensuring data privacy and collaboration with experts.

Lead cross-functional data science initiatives, prototype ML models, and enhance procurement optimization strategies while mentoring junior team members.

Lead development of machine learning models for real-time content ranking, translating business objectives into effective ML solutions while managing experiments and data pipelines.

Lead the development of credit risk models, collaborating with consultants and technology teams, and implement LLM-based agents for dynamic decision-making.