DATA SCIENTIST

This position is responsible for independently designing, implementing, and productionizing advanced analytics solutions that blend machine learning, simulation, and optimization to improve operational decision-making at Santee Cooper. The Data Scientist leads end-to-end delivery of moderately complex projects (e.g., improved load forecasting, asset health surrogate models, scheduling/dispatch optimizers), owns model quality and lifecycle, and partners closely with operations to deploy and monitor models in production with measurable business impact.

Essential Job Tasks:

• Leads end-to-end development of ML/DL models for forecasting, anomaly detection, classification, or surrogate modeling; evaluate trade offs and select appropriate algorithms.
• Designs and implement mid complexity optimization models (MILP/heuristics) and integrate them with learned models to support decision workflows (maintenance scheduling, dispatch, demand response).
• Develops simulation experiments and digital twin style workflows for scenario analysis and capacity planning.
• Build robust feature engineering pipelines and collaborate with data engineering to productionize datasets (feature stores, incremental pipelines).
• Applies and extends LLM capabilities for automation tasks (intelligent assistants, summarization, data augmentation) using safe prompt engineering and light fine-tuning where appropriate.
• Implements MLOps best practices: automated training, model versioning, CI/CD, monitoring, and alerting for drift/performance.
• Performs rigorous model validation: back testing, cross validation, uncertainty quantification, sensitivity analyses, and test data holding strategies.
• Documents models, assumptions, and provide reproducible artifacts and dashboards for stakeholders.

• Bachelor’s degree in Mathematics, Statistics, Computer Science or related field., * Bachelor’s degree in Mathematics, Statistics, Computer Science or related field + 2 years experience as an ETL Developer and/or Data Analyst.
• Must be proficient in Python (pandas, NumPy, scikit-learn; plus PyTorch/TensorFlow for DL; FastAPI/Flask for services; venv/poetry) and working familiarity with R for analysis when needed.