Principal Energy Storage Software Optimization Engineer - REMOTE

ThinkBAC Consulting

San Francisco, CA

Paid Time Off
Full-Time

Job Description

This is a remote position.

Lead Energy Storage Quantitative Software Optimization Engineer - Energy Trading

Location: FULLY REMOTE (Anywhere in the USA)

This is an opportunity to join an industry leading renewable energy venture with strong private equity backing that is focused on the development, execution, and operations of dynamic utility-scale energy storage projects. They are at the forefront of the industry, have accumulated over 9GW of projects in a relatively short period of time, and are currently in an accelerated expansion phase which includes key additions to their Software, Data, and Technology Team.

The Energy Storage Quantitative Software Optimization Engineer i s a Principal Engineer level role on an innovative team focused on ML / AI energy predictive pricing and quantitative forecasting models that will drive the algorithmic decision making process of next generation utility-scale renewable energy projects across all ISO / RTO markets in the United States. It will be part of a creative team focused on energy storage / battery storage energy trading strategies, asset management, and real-time energy pricing.

They are committed to creating more renewable infrastructure solutions for the grid and are offering comprehensive compensation packages to their employees leading the drive to meet company goals. Other perks included a competitive base salary, open PTO policy, flex work hours, benefits, the opportunity to work with a transparent Executive Leadership Team..and more.

RESPONSIBILITIES:

The Lead Quantitative Data Scientist / Software Optimization Engineer - Develops and implements quantitative predictive models for utility-scale renewables projects operating in wholesale electricity markets with a key focus on energy storage initiatives
The Lead Quantitative Data Scientist / Software Optimization Engineer - Develops, updates, and implements mixed-integer linear programming (MILP) optimization models for energy storage, asset management, and energy trading initiatives
The Lead Quantitative Data Scientist / Software Optimization Engineer - Creates, designs, & test multitasking time series forecast models in AWS Sagemakeer machine learning environment
The Lead Quantitative Data Scientist / Software Optimization Engineer - Utilize forward thinking techniques such as optimal control, deep learning, machine learning (AI/ML), and reinforcement learning to evaluate and update current protocols
The Lead Quantitative Data Scientist / Software Optimization Engineer - Drive the implementation of full-lifecycle ML/AI solutions and take ownership of real-time troubleshooting
The Lead Quantitative Data Scientist / Software Optimization Engineer - Optimization modeling to forecast congestion, assess congestion drivers, and assist in locational marginal pricing (LMP) assessments

QUALIFICATIONS:

8-10+ yrs of optimization based python programming, mixed-integer linear programming (MILP), stochastic optimization, & predictive modeling experience
Machine learning development experience in production ready coding environments focused on complex projects
Well versed in Python-based optimization toolkits such as Pyomo, CVXPY GurobiPy, etc.
Expert in Python stack - scipy, numpy, pandas, etc...
Experience working in APIs databases like SQL, NoSQL, and RESTful to a process and manipulate large datasets
Expertise in the Amazon Web Services (AWS) Sagemaker Machine Learning platform
Solid understanding convex optimization techniques (Linear/Mixed Integer programming) and time-series forecasting (PostgreSQL, TimescaleDB, InfluxDB)
Well versed in Bitbucket, git, or GitHub
Well versed in machine learning concepts such as classification, deep learning, deep neural networks (DNN), reinforcement learning, and regression problem solving techniques
HUGE PLUS - experience working in production ready coding environments in the energy trading or financial trading sector
HUGE PLUS - solid understanding of national energy markets and renewable energy portfolios - PJM, ERCOT, SPP, MISO, NYISO, ISO-NE, and CAISO; capacity prices, regional energy pricing, congestion and curtailment analysis, transmission constraints, interconnection assessments, LMPs (locational marginal pricing), and/or regional supply and demand curves)
Ideal candidates for this role will have experience working in Senior, Lead, Principal Engineer roles as Data Scientist, Quantitative Software Engineer, Stochastic Software Engineer, Computational Software Engineer Optimization Engineer....etc