Data Scientist

Job Title: Data Scientist - 01-5270**NO CTC- Please do not apply if you can't work directly for usMust be Local or willing to relocate from day one. Alternate weeks in Richmond VA office; other week remote. (5 days in office, 5 days remote, repeating). No 100% remoteRequired Emphasis on:Experience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectivesExpertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real world application experienceDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoringMUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasetsRequired Skills and ExperienceMUST have prior hands on experience as a Data Scientist on a project using Python or RProven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executivesAbility to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messagingDemonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumptionStrong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, imageWorking 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 environmentsWorking knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controlsExperience with cloud and modern analytics platforms (AWS, Azure, GCP, Snowflake, Databricks, or similar) is a strong plusUnderstanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferredSoft skill requirementsStrong communication skills both verbal and writtenAbility to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teamsNice to Have Skills:Understanding and/or Experience with data engineering is a plusExperience with cloud technologies(AWS, Azure, GCP, Snowflake) is big plusHigh Level Project Overview:This role serves as a technical consultant and senior individual contributor within our 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 casesDesign, build, and deploy predictive, prescriptive, and diagnostic models to support:Asset health and predictive maintenanceLoad forecasting and demand modelingOutage prediction, restoration optimization, and reliability analyticsGrid resilience, renewable integration, and emissions reduction initiativesCustomer behavior, billing, and energy efficiency programsApply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale dataDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoringSupport implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standardsCollaborate closely with data engineers, platform teams, and cloud architects to ensure models are production ready and performantBuild reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolioCreate intuitive visualizations, dashboards, and self-service analytics tools that empower stakeholders to explore insights independentlyMentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practicesSupport our commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AIRequired Years of Experience:MUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasetsEducation:Education: Bachelors or higher requiredDiscipline: Computer Science, Information Systems, MathematicsIdeal experience?High Preference for candidates that have previously worked with a large scale commercial utilities team but will review candidates who have a background with large scale capital projects for companiesLocation = Richmond VA (parking not provided)Rate = $50-$62.50/hr a W2 contractLength = 1+ Years W2 Contract - Possible long term/extension for the right candidate