Senior Data Scientist – Enterprise Analytics & Machine Learning (Hybrid)

Position OverviewWe are seeking a Senior Data Scientist to serve as a senior individual contributor and technical consultant. This role focuses on building scalable predictive and prescriptive analytics solutions that support grid reliability, modernization, customer experience, and clean energy initiatives. You will partner across business units, engineering, and platform teams to deliver production-grade machine learning solutions that drive measurable operational and financial impact.Must be located in or around Richmond, VAWe are unable to submit C2C or Visa transfer candidatesIdeal CandidateA hands-on senior data scientist who has built and deployed production ML systems in enterprise environmentsStrong problem-solver comfortable working with messy, large-scale, real-world operational dataSkilled in translating complex analytics into clear business impact for executive stakeholdersExperienced in end-to-end ML lifecycle ownership, including MLOps and production monitoringCollaborative, proactive, and able to influence across technical and non-technical teamsPassionate about applying analytics to improve operational reliability, efficiency, and sustainabilityKey ResponsibilitiesPartner with stakeholders across Generation, Transmission & Distribution, Operations, Asset Management, Customer Operations, and Finance to identify high-value analytics opportunitiesDesign and deploy ML solutions for asset health, predictive maintenance, forecasting and prediction, optimization, and customer analyticsApply advanced techniques, including time series forecasting, optimization, clustering, survival analysis, NLP, and anomaly detectionBuild end-to-end data science pipelines: data ingestion, feature engineering, modeling, validation, deployment, and monitoringImplement MLOps practices, including CI/CD, model versioning, governance, testing, and reproducibilityDevelop dashboards and self-service analytics using tools such as Power BI, Streamlit, Dash, or RShinyCommunicate insights and recommendations to both technical and executive audiencesMentor junior data scientists and support analytics best practices and standardsRequired QualificationsBachelor’s or master’s degree in Computer Science, Engineering, Math, Statistics, or related field5+ years of hands-on Data Science experience using Python or RStrong experience with large-scale, complex datasets (including time-series, sensor/SCADA, and unstructured data)Proven experience building and deploying enterprise ML solutionsStrong foundation in statistics, forecasting, optimization, anomaly detection, and MLExperience with data visualization and stakeholder communicationFamiliarity with MLOps tools and practices (e.g., MLflow, Azure ML, CI/CD, version control, monitoring)Understanding of model governance, explainability, drift detection, and data qualityPreferred QualificationsLarge infrastructure industry experienceCloud experience with AWS, Azure, GCP, Snowflake, or DatabricksExperience supporting operational analytics or capital projectsUnderstanding of enterprise governance, compliance, and security requirementsThe hourly rate for this position is $62.56.TM Floyd & Company is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.We offer a generous array of benefits, depending on the length of assignment. We also offer a referral bonus of up to $1,000. Ask us for more details!TM Floyd & Company participates in E-VERIFYAAP, EEO26-00271