Location: San Francisco (Hybrid in SF highly preferred, US only)
What is Verse?
Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.
Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.
The Role
Verse is seeking a Quantitative Analyst to join our Data Science Team. In this position, you will own research projects end-to-end from problem formulation through model development to production integration. Your work feeds directly into Aria and into decisions our customers make about how to procure, dispatch, and hedge their energy assets. For example, you might spend a cycle backtesting financial performance of renewable energy projects, encoding bespoke energy contract terms into reusable and scaled models, or developing a probabilistic model for medium-term energy price scenarios.
Key Responsibilities
- Model & Forecast: Build and improve models for renewable generation, storage dispatch, and energy price prediction using machine learning, statistical methods, and optimization techniques.
- Own Research Projects: Scope problems with product, engineering and customer teams, design solutions, validate results against industry benchmarks, and communicate findings clearly to both technical and non-technical audiences.
- Software Development & Productionization: Integrate research outputs into Verse’s cloud-based production environment; write clean, well-documented Python code and leverage AI coding tools to accelerate development.
- Develop Domain Expertise: Build foundational knowledge of electricity markets and renewable energy trends; develop an understanding of key drivers (e.g., load growth, market rule changes, and renewable deployment) and learn to incorporate relevant insights into renewable energy PPA modeling and analysis.
What We're Looking For (Minimum Qualifications)
- Master's degree in a quantitative field (engineering, computer science, economics, mathematics, operations research, physics, or similar); or
- Bachelor’s degree and 2+ years of energy sector experience
- Solid foundations in machine learning and statistical modeling
- Proficiency in Python, including scientific computing libraries (NumPy, pandas, scikit-learn)
- Familiarity with wholesale electricity market fundamentals and renewable energy technologies
- Ability to communicate technical findings clearly to both technical and non-technical audiences
What Will Make You Standout (Preferred Qualifications)
- Direct experience with US or European wholesale electricity markets or utility tariff structures
- Experience with energy procurement, power purchase agreements, or risk management
- Experience modeling the operational and/or economic behavior of solar, wind, or energy storage
- Foundational knowledge of mathematical optimization
- Experience shipping models to production in a commercial or research environment
- Experience developing probabilist