Job Opportunities API

Location: San Francisco, CA (Hybrid)  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 an experienced Senior Data Scientist, Infrastructure to join our Data Science Team. In this position, you will play a key role in advancing cutting-edge forecasting algorithms to support the operation of distributed battery storage, demand response, and renewable energy. This is a senior role where you will lead the design, development, and deployment of advanced machine learning models powering Verse software offerings related to distributed battery storage. You will work closely with other data science team members and software engineers to deliver production-grade machine learning solutions.Your research will help our customers deploy and operate renewable energy and battery storage resources, and will contribute to the transition toward a low-carbon economy. As a member of the Verse team, you will work in an interdisciplinary and collaborative environment where your expertise in machine learning, data science, and energy systems will be key to delivering impactful solutions. Key Responsibilities Machine Learning/Data Science: Apply machine learning, data science and statistical methods to advance Verse forecasting capability that is embedded in our software offerings. Forecasting Methods: Be responsible for forecasting workflows that inform optimization methods to control battery storage systems, demand response, and other types of electricity market participation. Statistical Analysis: Use statistical methods to support decision making under uncertainty. Data Analysis and Modeling: Use advanced data analysis techniques, simulations, and energy modeling tools to forecast and provide insights relative to the performance of renewable energy resources, battery storage, and novel technologies. Conduct Advanced Research: Lead and contribute to high-impact research focused on energy systems, including renewable energy (solar, wind, etc.), energy storage, and novel technologies (e.g. green hydrogen). Collaboration and Teamwork:  Work closely across business units and with our customers to share findings and ensure research outcomes are applied to real-world problems. What We're Looking For (Minimum Qualifications) At least 5 years of experience deploying machine learning forecasting algorithms in a production software environment.  Experience with machine learning, including deep learning, for time series forecasting and quantification of uncertainty. At least 2 years of experience applying forecasting methods in the energy industry. Proven expertise in machine learning, statistical methods, and forecasting methods applied to energy systems. Familiarity with electricity markets (US and global).  Knowledge of modern, state of the art ML forecasting methods. Deep knowledge of statistical methods and applications to real world problems. Highly proficient in Python programming and data analysis tools. Deep understanding of energy technologies, including solar, wind, battery storage, and grid integration. What Will Make You Sta