Principal Energy Storage Software Optimization Engineer - REMOTE

ThinkBAC Consulting; United States; Remote; USD 90,000 - 150,000; Full time

Job summary

Ein innovatives Unternehmen im Bereich erneuerbare Energien sucht einen Lead Energy Storage Quantitative Software Optimization Engineer. In dieser Schlüsselrolle werden Sie quantitative Modelle entwickeln, um die Entscheidungsfindung für großangelegte Energieprojekte zu unterstützen. Sie arbeiten in einem kreativen Team, das sich auf ML/AI-gestützte Preisprognosen und Handelsstrategien konzentriert. Diese Position bietet Ihnen die Möglichkeit, in einem dynamischen Umfeld zu arbeiten, das sich der Schaffung nachhaltiger Lösungen für die Energieinfrastruktur widmet. Genießen Sie flexible Arbeitszeiten und ein wettbewerbsfähiges Gehalt, während Sie an vorderster Front der Energiewende stehen.

Benefits

Flexibles Arbeitszeitmodell

Offene PTO-Politik

Umfassende Sozialleistungen

Transparente Führungsebene

Qualifications

• 8-10+ Jahre Erfahrung in der Optimierung und Programmierung mit Python.
• Erfahrung in der Entwicklung von maschinellen Lernmodellen in Produktionsumgebungen.

Responsibilities

• Entwicklung und Implementierung quantitativer Modelle für erneuerbare Energieprojekte.
• Optimierung von Energiehandelsstrategien und Asset-Management-Initiativen.

Skills

Python Programmierung

Mixed-Integer Linear Programming (MILP)

Stochastische Optimierung

Maschinelles Lernen (ML/AI)

Datenanalyse mit SQL

Zeitreihenprognose

Education

Bachelor in Informatik oder verwandtem Bereich

Master in Informatik oder verwandtem Bereich

Tools

AWS Sagemaker

Pyomo

CVXPY

GurobiPy

Bitbucket

GitHub

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 is 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 include a competitive base salary, open PTO policy, flex work hours, benefits, and the opportunity to work with a transparent Executive Leadership Team.

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, & tests multitasking time series forecast models in AWS Sagemaker machine learning environment.
• The Lead Quantitative Data Scientist / Software Optimization Engineer - Utilizes 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 - Drives the implementation of full-lifecycle ML/AI solutions and takes 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+ years 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 process and manipulate large datasets.
• Expertise in the Amazon Web Services (AWS) Sagemaker Machine Learning platform.
• Solid understanding of 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.