{"schemaVersion":"jobsearcher.job.v1","id":"bcb514a2a15bf05c586ed6c8","url":"https://jobsearcher.com/jobs/bcb514a2a15bf05c586ed6c8","canonicalUrl":"https://jobsearcher.com/jobs/bcb514a2a15bf05c586ed6c8","title":"Data Scientist","description":"Job Title: Data Scientist - 01-5270\n**NO CTC- Please do not apply if you can't work directly for us\nMust 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% remote\nRequired Emphasis on:\nExperience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectives\nExpertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real world application experience\nDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring\nMUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasets\nRequired Skills and Experience\nMUST have prior hands on experience as a Data Scientist on a project using Python or R\nProven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executives\nAbility to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messaging\nDemonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumption\nStrong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, image\nWorking 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)\nStrong understanding of model monitoring, including performance tracking, explainability, bias detection, model drift, and reproducibility in production environments\nWorking knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controls\nExperience with cloud and modern analytics platforms (AWS, Azure, GCP, Snowflake, Databricks, or similar) is a strong plus\nUnderstanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred\nSoft skill requirements\nStrong communication skills both verbal and written\nAbility to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams\nNice to Have Skills:\nUnderstanding and/or Experience with data engineering is a plus\nExperience with cloud technologies(AWS, Azure, GCP, Snowflake) is big plus\nHigh Level Project Overview:\nThis 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.\nKey responsibilities include:\nPartner with business units such as Generation, Transmission & Distribution, Grid Operations, Asset Management, Customer Operations, and Finance to identify high value data science use cases\nDesign, build, and deploy predictive, prescriptive, and diagnostic models to support:\nAsset health and predictive maintenance\nLoad forecasting and demand modeling\nOutage prediction, restoration optimization, and reliability analytics\nGrid resilience, renewable integration, and emissions reduction initiatives\nCustomer behavior, billing, and energy efficiency programs\nApply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale data\nDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring\nSupport implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standards\nCollaborate closely with data engineers, platform teams, and cloud architects to ensure models are production ready and performant\nBuild reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolio\nCreate intuitive visualizations, dashboards, and self-service analytics tools that empower stakeholders to explore insights independently\nMentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practices\nSupport our commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI\nRequired Years of Experience:\nMUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasets\nEducation:\nEducation: Bachelors or higher required\nDiscipline: Computer Science, Information Systems, Mathematics\nIdeal experience?\nHigh 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 companies\nLocation = Richmond VA (parking not provided)\nRate = $50-$62.50/hr a W2 contract\nLength = 1+ Years W2 Contract - Possible long term/extension for the right candidate\nJob Types: Full-time, Contract\nPay: $55.00 - $62.50 per hour\nEducation:\nBachelor's (Required)\nExperience:\nData science: 5 years (Required)\nPython or R: 5 years (Required)\ncreating interactive dashboards: 3 years (Preferred)\nMLOps: 2 years (Preferred)\nWork Location: Hybrid remote in Richmond, VA 23219","company":"Nationalcomputinggroup","rawCompany":"nationalcomputinggroup","city":"Henrico","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-07-20T11:45:15.813Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.01","title":"Business Intelligence Analysts","slug":"business-intelligence-analysts"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Scientist","description":"Job Title: Data Scientist - 01-5270\n**NO CTC- Please do not apply if you can't work directly for us\nMust 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% remote\nRequired Emphasis on:\nExperience designing, developing, and deploying advanced analytics and machine learning solutions aligned to business objectives\nExpertise across machine learning, statistical modeling, forecasting, optimization, and anomaly detection, with real world application experience\nDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring\nMUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasets\nRequired Skills and Experience\nMUST have prior hands on experience as a Data Scientist on a project using Python or R\nProven ability to translate complex analytical findings into clear, actionable insights for business leaders, engineers, operations teams, and executives\nAbility to create clear, interpretable visualizations that tell a compelling story, support decision making, and align with executive level messaging\nDemonstrated experience creating interactive dashboards, reports, and applications (e.g., RShiny, Power BI, Streamlit, Dash) for business consumption\nStrong experience working with structured, semi structured, and unstructured data (e.g., sensor/SCADA data, time series data, text, image\nWorking 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)\nStrong understanding of model monitoring, including performance tracking, explainability, bias detection, model drift, and reproducibility in production environments\nWorking knowledge of data engineering concepts, including data ingestion, transformation, feature engineering, and data quality controls\nExperience with cloud and modern analytics platforms (AWS, Azure, GCP, Snowflake, Databricks, or similar) is a strong plus\nUnderstanding of governance, security, and regulatory requirements for enterprise and utility data environments is preferred\nSoft skill requirements\nStrong communication skills both verbal and written\nAbility to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams\nNice to Have Skills:\nUnderstanding and/or Experience with data engineering is a plus\nExperience with cloud technologies(AWS, Azure, GCP, Snowflake) is big plus\nHigh Level Project Overview:\nThis 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.\nKey responsibilities include:\nPartner with business units such as Generation, Transmission & Distribution, Grid Operations, Asset Management, Customer Operations, and Finance to identify high value data science use cases\nDesign, build, and deploy predictive, prescriptive, and diagnostic models to support:\nAsset health and predictive maintenance\nLoad forecasting and demand modeling\nOutage prediction, restoration optimization, and reliability analytics\nGrid resilience, renewable integration, and emissions reduction initiatives\nCustomer behavior, billing, and energy efficiency programs\nApply advanced techniques such as time series forecasting, survival analysis, optimization, clustering, NLP, and anomaly detection to utility scale data\nDevelop end to end data science solutions, from data acquisition and feature engineering to model deployment and post production monitoring\nSupport implementation of MLOps best practices to ensure scalable, reliable, and auditable analytics solutions in compliance with enterprise and regulatory standards\nCollaborate closely with data engineers, platform teams, and cloud architects to ensure models are production ready and performant\nBuild reusable analytical frameworks and accelerators that improve time to value across the Enterprise Analytics portfolio\nCreate intuitive visualizations, dashboards, and self-service analytics tools that empower stakeholders to explore insights independently\nMentor junior data scientists and analysts, contributing to analytics standards, code quality, and best practices\nSupport our commitment to safety, reliability, affordability, and clean energy transformation through responsible and ethical use of data and AI\nRequired Years of Experience:\nMUST have 5+ years of experience in Data Science using Python or R, with a strong focus on analyzing large, complex, and high-volume datasets\nEducation:\nEducation: Bachelors or higher required\nDiscipline: Computer Science, Information Systems, Mathematics\nIdeal experience?\nHigh 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 companies\nLocation = Richmond VA (parking not provided)\nRate = $50-$62.50/hr a W2 contract\nLength = 1+ Years W2 Contract - Possible long term/extension for the right candidate\nJob Types: Full-time, Contract\nPay: $55.00 - $62.50 per hour\nEducation:\nBachelor's (Required)\nExperience:\nData science: 5 years (Required)\nPython or R: 5 years (Required)\ncreating interactive dashboards: 3 years (Preferred)\nMLOps: 2 years (Preferred)\nWork Location: Hybrid remote in Richmond, VA 23219","datePosted":"2026-07-20T11:45:15.813Z","dateModified":"2026-07-20T11:45:15.813Z","hiringOrganization":{"@type":"Organization","name":"Nationalcomputinggroup","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Henrico","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bcb514a2a15bf05c586ed6c8"},"url":"https://jobsearcher.com/jobs/bcb514a2a15bf05c586ed6c8"}}