Pursuing a bachelor’s degree or higher in engineering, applied mathematics, or a closely related field
Experience with Python libraries for numerical methods and timeseries data (NumPy, Pandas, SciPy)
Some experience in Linear Programming, Mixed Integer Programming, and/or Convex Optimization experience with collaborative coding and ability to write clean, maintainable, and well documented code
Strong communication and interpersonal skills
Ability to understand and explain complex problems simply and effectively
Bonus Qualifications:
We would love to hire someone who has:
Experience with optimization modeling packages such as PYOMO, CVXPY, or solver APIs (e.g. Gurobi, Cplex)
Domain-specific knowledge either through previous work, courses in college, or side projects
Experience working with SQL and data visualization tools
Responsibilities
Develop optimization and control algorithms from the ground up which includes:
Collaborate with modeling and controls engineers to understand requirements and market rules (e.g. electricity tariffs)
Translate requirements into energy scheduling and dispatch optimization models and define objectives for different use cases (e.g. peak shaving, cost minimization)
Contribute to the development and maintenance of our simulation codebase for evaluating algorithm performance
Conduct batch simulation experiments to tune models and parameters for maximum performance
Collaborate with Data Scientists on requirements for inputs to the optimization (e.g. scenario selection, time series forecasting)
Integrate developed algorithms in our production code base with robust test coverage
Write Python code to manipulate and analyze timeseries data