

nTech Workforce
Data Scientist (ML & Operational Analytics)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist (ML & Operational Analytics) on a 12-month W2 contract, hybrid in Washington, DC. Requires a Master’s degree, 5+ years in data science, proficiency in Python, R, SQL, and operational analytics experience, preferably in the electric utility sector.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 28, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Washington, DC
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🧠 - Skills detailed
#Forecasting #Data Quality #Python #R #ML (Machine Learning) #Deployment #Classification #Libraries #Computer Science #Data Lifecycle #Programming #Azure Machine Learning #Regression #Mathematics #Statistics #Quality Assurance #Data Science #Azure #SQL (Structured Query Language)
Role description
•
•
•
• This is NOT A C2C position'
•
•
•
• Title: Data Scientist (ML& Operational Analytics)
Location: Hybrid in Washington, DC
Terms of Employment
• W2 Contract, 12 Months
• This is a hybrid opportunity at Washington, DC (Local candidates only)
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
•
•
•
• This is NOT A C2C position'
•
•
•
• Title: Data Scientist (ML& Operational Analytics)
Location: Hybrid in Washington, DC
Terms of Employment
• W2 Contract, 12 Months
• This is a hybrid opportunity at Washington, DC (Local candidates only)
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





