KamisPro
Senior Data Scientist – Optimization (Energy Systems)
KamisPro, Baltimore, Maryland, United States, 21276
Senior Data Scientist – Optimization (Energy Systems)
We are seeking a Senior Data Scientist with deep experience in MILP-based optimization to build, scale, and improve decision-optimization and forecasting systems for complex energy use cases. This role is embedded within the Product team and focuses on extending a production optimization engine, improving solution accuracy, and enabling new programs and constraints across energy systems and distributed energy resources (DERs). This is a hands‑on, senior role for candidates with a strong operations research foundation, experience using Python and Pyomo, and the ability to translate business objectives into scalable optimization solutions.
What You’ll Do
Design, prototype, and implement enhancements to a MILP-based optimization engine
Extend core data models and optimization formulations to support new use cases, programs, and constraints
Integrate and scale optimization logic with solvers and production systems
Benchmark optimization performance across program stacks, load profiles, locations, and other key variables
Build robust test coverage for new and existing optimization logic
Monitor optimization accuracy at the customer‑site level and proactively identify anomalies
Diagnose root causes of optimization accuracy issues and propose product improvements
Collaborate with product, engineering, and business stakeholders to align optimization and forecasting with economic objectives
Analyze market price behavior and propose strategies to improve asset utilization
Quantify the incremental value of optimization changes to support product prioritization
Identify new data science‑led opportunities and incorporate internal and external data sources
Contribute to building and scaling a data science and optimization practice over time
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Operations Research, Mathematics, Statistics, Engineering, Physics, or a related field
7+ years of experience in data science, optimization, or a related quantitative field
2–5+ years of hands‑on experience with MILP-based optimization (professional experience preferred; advanced academic experience acceptable)
Strong proficiency in Python and Pyomo, with experience implementing optimization models in production
Experience with mixed‑integer optimization techniques and solver integration
Knowledge of time‑series forecasting and machine learning methods (e.g., ARIMA, LSTM, probabilistic models)
Experience with model predictive control or sequential decision‑making systems
Experience working in Agile, cross‑functional product development environments
Ability to clearly communicate technical concepts and manage stakeholder expectations
Authorization to work in the United States without current or future visa sponsorship
Preferred Qualifications
Experience with electricity markets, utility tariffs, and interval data
Familiarity with DER assets such as batteries, solar, and backup generation
Experience forecasting energy prices, system peaks, or demand response events
Advanced experience with Azure, Postgres, or similar cloud/data platforms
Software development experience in Python and/or .NET
Experience building or leading a data science or optimization practice
Why Join Us
Work on real‑world, large‑scale optimization problems with direct business impact
Collaborate with experienced product and engineering teams in a growing organization
Gain deep exposure to energy systems, DER optimization, and electricity markets
Competitive compensation and comprehensive benefits including medical, dental, vision, 401(k), vacation, and up to $10,000/year in tuition reimbursement
#J-18808-Ljbffr
What You’ll Do
Design, prototype, and implement enhancements to a MILP-based optimization engine
Extend core data models and optimization formulations to support new use cases, programs, and constraints
Integrate and scale optimization logic with solvers and production systems
Benchmark optimization performance across program stacks, load profiles, locations, and other key variables
Build robust test coverage for new and existing optimization logic
Monitor optimization accuracy at the customer‑site level and proactively identify anomalies
Diagnose root causes of optimization accuracy issues and propose product improvements
Collaborate with product, engineering, and business stakeholders to align optimization and forecasting with economic objectives
Analyze market price behavior and propose strategies to improve asset utilization
Quantify the incremental value of optimization changes to support product prioritization
Identify new data science‑led opportunities and incorporate internal and external data sources
Contribute to building and scaling a data science and optimization practice over time
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Operations Research, Mathematics, Statistics, Engineering, Physics, or a related field
7+ years of experience in data science, optimization, or a related quantitative field
2–5+ years of hands‑on experience with MILP-based optimization (professional experience preferred; advanced academic experience acceptable)
Strong proficiency in Python and Pyomo, with experience implementing optimization models in production
Experience with mixed‑integer optimization techniques and solver integration
Knowledge of time‑series forecasting and machine learning methods (e.g., ARIMA, LSTM, probabilistic models)
Experience with model predictive control or sequential decision‑making systems
Experience working in Agile, cross‑functional product development environments
Ability to clearly communicate technical concepts and manage stakeholder expectations
Authorization to work in the United States without current or future visa sponsorship
Preferred Qualifications
Experience with electricity markets, utility tariffs, and interval data
Familiarity with DER assets such as batteries, solar, and backup generation
Experience forecasting energy prices, system peaks, or demand response events
Advanced experience with Azure, Postgres, or similar cloud/data platforms
Software development experience in Python and/or .NET
Experience building or leading a data science or optimization practice
Why Join Us
Work on real‑world, large‑scale optimization problems with direct business impact
Collaborate with experienced product and engineering teams in a growing organization
Gain deep exposure to energy systems, DER optimization, and electricity markets
Competitive compensation and comprehensive benefits including medical, dental, vision, 401(k), vacation, and up to $10,000/year in tuition reimbursement
#J-18808-Ljbffr