Data Scientist

Job at a Glance

• Title: Data Scientist
• Location: Richmond VA (alternating weeks in-office and remote)
• Contract: W2 only, 12 month contract with potential for extension or conversion to full time with either the client or CEI
• Pay: $52-$62 /hour + optional medical, dental, vision, 401(k) match

Overview

This role serves as a technical consultant and senior individual contributor within our client''s Enterprise Data Analytics team, delivering advanced analytics and data science solutions that support operational reliability, grid modernization, customer experience, and clean energy initiatives. The position involves partnering with various business units to identify high-value data science use cases and deploying predictive, prescriptive, and diagnostic models to support asset health, load forecasting, outage prediction, grid resilience, and customer behavior analysis.

Key Responsibilities

• 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 closely with data engineers, platform teams, and cloud architects to ensure models are production-ready and performant.
• Evaluate model performance continuously, identify data/model drift, and recommend retraining or enhancement strategies.
• 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’s commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI.

Required Skills

• 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.
• Experience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectives.
• 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, images).
• Expertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real-world application experience.
• Experience or 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.
• Experience or 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, GCP, Snowflake, Databricks, or similar) is a strong plus.
• Understanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred.
• Strong communication skills both verbal and written.
• Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams.

Preferred Skills

• Understanding and/or experience with data engineering is a plus.
• Experience with cloud technologies (AWS, Azure, GCP, Snowflake) is a big plus.

Why Should I Apply?

This position offers the opportunity to work on impactful projects supporting utility-scale data science initiatives, with a focus on energy reliability and clean energy transformation. Candidates will engage with cutting-edge technologies and collaborate across diverse teams to deliver innovative solutions.

About CEI:

As a trusted technology partner, CEI delivers solutions that help our customers transform their business and achieve meaningful results. From strategy and custom application development through application management - our technology and digital experience services are tailored to meet each unique need of our customers. Our staffing solutions bring specialized skills to complement our customers'' workforce and project requirements.

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