Quantitative Scientist​/Sr - Power Markets

Overview

Equilibrium Energy is a team of technologists, power market experts, and AI pioneers reimagining how the world's most critical industry operates. We're building a first-of-its-kind AI operating system for the power sector, uniting cutting-edge science with real-world purpose to enable a cleaner, more resilient energy future. At EQ, you'll join a tight-knit group of brilliant, curious, and adventurous people who bring the same energy to collaboration as they do to innovation.

Equilibrium Energy is a well-funded, Series B clean energy startup backed by some of the most prominent institutional investors in climate. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We're looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.

Equilibrium was founded with a vision for building a company where innovation, collaboration, machine learning, and data science power all aspects of our algorithmic decision-making. We are looking for staff / sr staff quantitative scientists with a heavy focus on trading strategy research and development in the energy space to accelerate the maturation of our quantitative trading & platform-as-a-service businesses. You'll help to shape the science-driven products, tools, & processes that will drive the future success of our company and lead the energy transition.

Use research insights to shape product direction and deliver innovative client solutions:
Influence product and engineering roadmaps through presentation of research insights, experimental results, and trading strategy backtest metrics, in order to evolve organizational direction and drive positive impact at EQ's clients. Initiate and lead cross-functional engagements to surface, prioritize, and structure advanced novel quantitative analytics or machine learning techniques that can drive outsized impact on company trading strategies and client solutions.

Trading performance analytics:
Investigate driving factors in trading over/under performance, identifying learnings, and drive a fly-wheel of continuous strategy improvement and team education.

Research, develop, backtest, and deploy novel quantitative trading signals and strategies in the energy domain:
Identify and extract sources of trading alpha by researching multiple energy datasets, surveying industry techniques & domain intuition, and executing hands-on experimental models & backtests. Drive the design, specification, development, and production deployment of our suite of novel quantitative trading solutions. Lead short to medium term research projects that advance the state-of-the-art in quantitative research techniques, as applied to energy asset management and financial trading.

• Passion for clean energy and fighting climate change
• An degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline
• 2+ years experience in quantitative research & analytics or systematic financial trading, or similar role, in the US Power Markets
• 2+ years experience with python and the supporting computational science tool suite (e.g. numpy, scipy, pandas, scikit-learn, tensor flow, etc)
• Experience in the electricity and energy domain (e.g. wholesale market prices)
• Experience developing, releasing, and tracking performance of quantitative trading strategies in production
• Experience communicating mathematical concepts, analytical results, and data-driven insights to both technical and non-technical audiences
• A collaboration-first mentality, with a willingness to teach as well as learn from others

• Experience designing and building novel statistical models on time series data, including characterizing probabilistic outcome uncertainty
• Experience with database technologies and sql
• Experience with probability, hypothesis testing, and uncertainty quantification
• Experienc…