Senior Data Scientist

Job Description

We are seeking a Senior Data Scientist to join Dominion Energy’s Enterprise Data Analytics team in Richmond, VA. This role will serve as a technical consultant and senior individual contributor responsible for delivering advanced analytics and machine learning solutions that support operational reliability, grid modernization, customer experience, and clean energy initiatives. The ideal candidate will have strong hands-on experience in Python or R, building and deploying end-to-end data science solutions using large, complex, and high-volume datasets. Candidates should possess expertise in forecasting, machine learning, optimization, anomaly detection, and predictive analytics, with demonstrated experience implementing production-grade ML solutions and MLOps best practices. This role will collaborate closely with business stakeholders, data engineers, cloud architects, and platform teams to design scalable analytics solutions that drive business value across utility operations.

Requirements

• 5+ years of hands-on experience as a Data Scientist using Python or R
• Experience working with large, complex, high-volume datasets in production environments
• Strong expertise in machine learning, statistical modeling, forecasting, optimization, and anomaly detection
• Experience designing and deploying end-to-end data science solutions from data acquisition through model monitoring
• Hands-on experience with MLOps tools such as MLflow, Azure ML, Dataiku, or similar platforms
• Experience with CI/CD pipelines, automated testing, model versioning, and production deployment
• Strong understanding of model monitoring, explainability, model drift, bias detection, and reproducibility
• Experience working with structured, semi-structured, and unstructured data
• Experience creating dashboards and interactive applications using Power BI, Streamlit, Dash, or RShiny
• Strong communication and stakeholder management skills
• Ability to translate analytical findings into actionable business insights
• Experience collaborating within cross-functional and multi-disciplinary teams
• Bachelor’s degree or higher in Computer Science, Mathematics, Information Systems, or related field
• USC or GC only
• Utility industry experience preferred
• Experience with cloud platforms such as AWS, Azure, GCP, Snowflake, or Databricks is a plus
• Data engineering knowledge is a plus

Responsibilities

• Partner with business units to identify high-value data science opportunities
• Design, build, and deploy predictive, prescriptive, and diagnostic analytics models
• Develop solutions for asset health monitoring and predictive maintenance
• Build load forecasting and demand prediction models
• Support outage prediction, restoration optimization, and reliability analytics initiatives
• Develop analytics solutions for grid resilience and renewable energy integration
• Analyze customer behavior, billing, and energy efficiency program data
• Apply time series forecasting, optimization, clustering, NLP, and anomaly detection techniques
• Develop end-to-end ML pipelines including feature engineering and deployment workflows
• Implement MLOps best practices for scalable and reliable analytics solutions
• Collaborate with data engineers and cloud teams to productionize models
• Create reusable analytics frameworks and accelerators
• Develop dashboards, visualizations, and self-service analytics applications
• Mentor junior data scientists and analysts
• Ensure compliance with enterprise governance and regulatory standards

Technologies & Skills

Benefits

• Competitive W2 hourly compensation
• Long-term contract opportunity
• Hybrid work environment
• Opportunity to work on enterprise-scale analytics initiatives
• Exposure to utility and clean energy transformation projects
• Collaborative and innovative team environment
• Hands-on experience with advanced analytics and cloud technologies