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

Position Overview We 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, VA • We are unable to submit C2C or Visa transfer candidates Ideal Candidate • A hands-on senior data scientist who has built and deployed production ML systems in enterprise environments • Strong problem-solver comfortable working with messy, large-scale, real-world operational data • Skilled in translating complex analytics into clear business impact for executive stakeholders • Experienced in end-to-end ML lifecycle ownership, including MLOps and production monitoring • Collaborative, proactive, and able to influence across technical and non-technical teams • Passionate about applying analytics to improve operational reliability, efficiency, and sustainability Key Responsibilities • Partner with stakeholders across Generation, Transmission & Distribution, Operations, Asset Management, Customer Operations, and Finance to identify high-value analytics opportunities • Design and deploy ML solutions for asset health, predictive maintenance, forecasting and prediction, optimization, and customer analytics • Apply advanced techniques, including time series forecasting, optimization, clustering, survival analysis, NLP, and anomaly detection • Build end-to-end data science pipelines: data ingestion, feature engineering, modeling, validation, deployment, and monitoring • Implement MLOps practices, including CI/CD, model versioning, governance, testing, and reproducibility • Develop dashboards and self-service analytics using tools such as Power BI, Streamlit, Dash, or RShiny • Communicate insights and recommendations to both technical and executive audiences • Mentor junior data scientists and support analytics best practices and standards Required Qualifications • Bachelor’s or master’s degree in Computer Science, Engineering, Math, Statistics, or related field • 5+ years of hands-on Data Science experience using Python or R • Strong experience with large-scale, complex datasets (including time-series, sensor/SCADA, and unstructured data) • Proven experience building and deploying enterprise ML solutions • Strong foundation in statistics, forecasting, optimization, anomaly detection, and ML • Experience with data visualization and stakeholder communication • Familiarity with MLOps tools and practices (e.g., MLflow, Azure ML, CI/CD, version control, monitoring) • Understanding of model governance, explainability, drift detection, and data quality Preferred Qualifications • Large infrastructure industry experience • Cloud experience with AWS, Azure, GCP, Snowflake, or Databricks • Experience supporting operational analytics or capital projects • Understanding of enterprise governance, compliance, and security requirements The 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-VERIFY AAP, EEO 26-00271