MUST CURRENTLY RESIDE IN DC AREA
12-Month Contract - potential to extend (max 2yrs)
In-Person Interviews - 2 Rounds
W2 (no C2C Options)
Salary Range: $85-$95/hr plus benefits after 90 days (healthcare/401k)
Hybrid Work Model: Tuesday-Thursday In Office (3 days) (Monday & Friday WFH)
Senior Data Scientist -- ML & Operational Analytics for Major Utility Client
📍 Washington, DC (Hybrid)
This role is on the Business Side (not IT)
We are seeking a Senior Data Scientist to join a high‑impact analytics team focused on machine learning, operational analytics, and data‑driven decision support. This role applies advanced statistical and ML techniques to large‑scale, complex datasets to generate insights that directly inform business and operational outcomes.
This is a great opportunity for a data scientist who enjoys working end‑to‑end---from data preparation and modeling to validation and deployment---while collaborating closely with business and technical stakeholders.
What You'll Do
- Apply the scientific method to extract insights from diverse data sources , including time‑series (smart meters, smart grid, IoT), structured, and unstructured data
- Build, validate, and deploy machine learning models (regression, classification, and time‑series forecasting) for real‑world operational use cases
- Perform data preparation, feature engineering, cleansing, and standardization across large and complex datasets
- Mine both large‑scale and small datasets using advanced statistical analysis and machine learning techniques
- Translate analytical findings into clear, actionable insights for business and operational stakeholders
- Collaborate closely with data engineers, information architects, project and program managers, and business partners
- Ensure data quality and model reliability throughout the development lifecycle
- Serve as a subject matter expert in AI, machine learning, feature engineering, and data mining
- Share knowledge, best practices, and insights with team members, business stakeholders, and IT partners
- Develop novel insights using statistical modeling and ML techniques on datasets ranging from terabytes to petabytes
Required Qualifications
- Master's degree in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field
- 5 years of experience in data science with a focus on operational analytics
- Strong proficiency in Python, R, SQL, and common machine learning libraries
- Solid foundation in statistics (probability, inference, regression, experimental design)
- Experience working across the full analytics lifecycle, from data ingestion to model deployment
Preferred Qualifications
- PhD in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field
- Experience in the electric utility or similar regulated, asset‑intensive industry
- Experience using Azure Machine Learning for model development and deployment
- Exposure to optimization techniques, including linear programming and mixed‑integer optimization