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Terms of Employment
W2 Contract, 12 Months
This is a hybrid opportunity at Washington, DC (Local candidates only) (Monday & Friday remote; Tues - thurs onsite)
Overview
Our client is seeking a Senior Data Scientist -ML & Operational Analytics to join their team in Washington, DC. This role is focused on the end-to-end development and deployment of machine learning models to drive operational efficiency. The successful candidate will bridge the gap between complex data theory and practical application, ensuring that models for regression, classification, and time-series analysis are integrated effectively into operational workflows.
Responsibilities
Design, build, and deploy high-quality machine learning models, including regression, classification, and time-series forecasting, to address specific operational use cases.
Manage the full data lifecycle, including data preparation, advanced feature engineering, and rigorous data quality assurance.
Monitor model performance and iterate on existing algorithms to improve accuracy and business impact.
Communicate complex analytical findings and statistical insights to stakeholders in a clear, actionable manner.
Required Skills & Experience
Master s degree in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.
5 or more years of professional experience in data science with a specific focus on operational analytics.
Advanced proficiency in Python, R, and SQL, along with extensive experience using standard machine learning libraries.
Deep statistical foundation with expertise in probability, inference, regression, and experimental design.
Exceptional problem-solving abilities and the capacity to work effectively within a collaborative team environment
Preferred Skills & Experience
PhD in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.
Experience within the electric utility industry or a similar industrial sector.
Hands-on experience utilizing Azure Machine Learning for the development and deployment of models.
Familiarity with optimization techniques, including linear programming and mixed-integer optimization
- Candidates must be local to Washington, DC
- This is a W2 position.
Terms of Employment
W2 Contract, 12 Months
This is a hybrid opportunity at Washington, DC (Local candidates only) (Monday & Friday remote; Tues - thurs onsite)
Overview
Our client is seeking a Senior Data Scientist -ML & Operational Analytics to join their team in Washington, DC. This role is focused on the end-to-end development and deployment of machine learning models to drive operational efficiency. The successful candidate will bridge the gap between complex data theory and practical application, ensuring that models for regression, classification, and time-series analysis are integrated effectively into operational workflows.
Responsibilities
Design, build, and deploy high-quality machine learning models, including regression, classification, and time-series forecasting, to address specific operational use cases.
Manage the full data lifecycle, including data preparation, advanced feature engineering, and rigorous data quality assurance.
Monitor model performance and iterate on existing algorithms to improve accuracy and business impact.
Communicate complex analytical findings and statistical insights to stakeholders in a clear, actionable manner.
Required Skills & Experience
Master s degree in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.
5 or more years of professional experience in data science with a specific focus on operational analytics.
Advanced proficiency in Python, R, and SQL, along with extensive experience using standard machine learning libraries.
Deep statistical foundation with expertise in probability, inference, regression, and experimental design.
Exceptional problem-solving abilities and the capacity to work effectively within a collaborative team environment
Preferred Skills & Experience
PhD in Computer Science, Statistics, Mathematics, Engineering, Physics, or a related quantitative field.
Experience within the electric utility industry or a similar industrial sector.
Hands-on experience utilizing Azure Machine Learning for the development and deployment of models.
Familiarity with optimization techniques, including linear programming and mixed-integer optimization