Data Scientist

Title: Data Scientist
Location: Richmond, VA - Hybrid
Duration: 12+ Months

Required Emphasis on:

• Experience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectives
• Expertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real world application experience
• Develop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring
• MUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasets

High Level Project Overview:

This role serves as a technical consultant and senior individual contributor within client Enterprise Data Analytics team, delivering advanced analytics and data science solutions that support operational reliability, grid modernization, customer experience, and clean energy initiatives.

Key responsibilities include:

• Partner with business units such as Generation, Transmission & Distribution, Grid Operations, Asset Management, Customer Operations, and Finance to identify high value data science use cases
• Design, build, and deploy predictive, prescriptive, and diagnostic models to support:
• Asset health and predictive maintenance
• Load forecasting and demand modeling
• Outage prediction, restoration optimization, and reliability analytics
• Grid resilience, renewable integration, and emissions reduction initiatives
• Customer behavior, billing, and energy efficiency programs
• Apply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale data
• Develop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring
• Support implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standards
• Collaborate with data engineers, platform teams, and cloud architects to ensure models are production ready and performant
• Build reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolio
• Create intuitive visualizations, dashboards, and self-service analytics tools that empower stakeholders to explore insights independently
• Mentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practices
• Support Dominion Energy commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI

Education:

• Education: Bachelors or higher required
• Discipline: Computer Science, Information Systems, Mathematics

Required Skills and Experience

• MUST have prior hands-on experience as a Data Scientist on a project using Python or R
• Proven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executives
• Ability to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messaging
• Demonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumption
• Strong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, image
• Working knowledge of MLOps practices including model development lifecycle management, automated testing, CI/CD pipelines, version control, and deployment (e.g., MLflow, Dataiku, Azure ML, or similar tools)
• Strong understanding of model monitoring, including performance tracking, explainability, bias detection, model drift, and reproducibility in production environments
• Working knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controls
• Experience with cloud and modern analytics platforms (AWS, Azure, Google Cloud Platform, Snowflake, Databricks, or similar) is a strong plus
• Understanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred

Nice to Have Skills:

• Understanding and/or Experience with data engineering is a plus
• Experience with cloud technologies(AWS, Azure, Google Cloud Platform, Snowflake) is big plus

Regards

Tim Patten

tim (at) pullskill (dot) com

551-272-o2o3