Senior Energy Optimization Engineer

Job description

Description

The Role

The Energy Optimization Engineer will be a key contributor to the design, development and maintenance of algorithms that operate Tesla’s energy assets and products in competitive energy markets. The ideal candidate brings experience building optimization models and applying those models to real-world challenges, ideally in the energy industry. The Optimization Engineer’s skillset must be complemented with a deep passion for data science, and a voracious appetite to continuously learn new techniques and methods and apply them towards our mission of accelerating society’s transition to a more sustainable energy future.

The candidate will join the Energy Optimization team that is broadly responsible for optimizing Tesla’s growing portfolio of distributed energy resources and utility-scale storage internationally. The portfolio of assets under management covers the full range of grid applications, end-users and global market geographies. In this function, the team works at the intersection of engineering, product development, business development, finance and policy.Externally, the team works closely with market operators, utilities, regulators, and commercial partners to implement solutions that are often first-of-a-kind.

Responsibilities

·  Architect and review economic optimization models that drive operations and battery monetization performance, including strategies applied to wholesale market participation, peak demand shaving, and electric vehicle charging.
·  Perform statistical analysis and develop machine-learning models for forecasting, visualization and economic evaluation of energy applications
·  Monitor, gather, clean, and validate internal and external data sets that are critical inputs to our algorithm ecosystem
·  Develop and maintain production-grade software that is highly reliable, computationally-efficient and integrated into Tesla’s energy products software ecosystem
·  Support continuous development algorithm processes by working cross functionally with a broad set of internal stakeholders
·  Liaison with internal partner teams to identify key policy and DER market design objectives based on operational experience

Desired profile

Requirements

·  Experience developing machine learning models and executing statistical analyses in order to solve operational problems or challenges. Experience with programming these models in Python is a must.
·  Experience in theory and application of optimization methods such as linear programming (LP) and mixed-integer programming (MIP) models in the energy industry, ideally in competitive wholesale markets.
·  Understanding of electric power generation, energy storage, transmission, and power dispatch modeling such as security-constrained unit commitment (SCUC)
·  Experience with optimization model formulation languages and solvers such as cvxpy, Xpress, Gurobi etc. is a plus
·  3-5 years working directly in the energy industry or on relevant types of problems in academia
·  Typical academic credentials include an MS or PhD in disciplines like Operations Research, Statistics, Mechanical/Electrical/Industrial Engineering, Applied Mathematics
·  Expert level Python programmer and proficient in MATLAB. Familiarity with R is considered a positive.
·  Direct experience in energy storage dispatch, production cost modeling, energy resource dispatch and energy procurement is a plus.
·  Previous experience at an ISO/RTO market operator, utility, merchant power producer, energy trading firm or other energy market participant is strongly preferred.
·  Ability to articulate deep technical topics effectively to both a generally technically savvy audience and a deep mathematically-oriented audience is preferred
·  Ability to work well in a collaborative culture, including brainstorming algorithm strategies, pair programming with software engineers, and reviewing code within the immediate team

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