Senior Data Scientist, Infrastructure

Verse; San Francisco (CA); On-site; USD 190,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation and equity grant

Comprehensive health benefits

Flexible hours and unlimited PTO

Diverse and inclusive work environment

Job summary

Verse is seeking a Senior Data Scientist, Infrastructure, to advance forecasting algorithms in renewable energy and battery storage. This senior role involves leading the design and deployment of machine learning models that support our software offerings and help customers operate renewable energy resources.

The ideal candidate will have a strong background in machine learning, statistics, and energy systems, with at least 5 years of experience in production environments. We offer a competitive salary range of $190,000 - $230,000 and a comprehensive benefits package.

Qualifications

• At least 5 years of experience in deploying machine learning forecasting algorithms in production.
• Experience with deep learning for time series forecasting.
• 2+ years in the energy industry applying forecasting methods.

Responsibilities

• Apply machine learning and statistical methods to advance forecasting capabilities.
• Lead research on energy systems including renewable energies and energy storage.
• Collaborate across business units to apply research findings.

Skills

Machine learning forecasting algorithms

Statistical methods

Python programming

Data analysis tools

Education

PhD in Engineering, Operations Research, Economics or related field

Job description

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.

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 year(s) 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 year(s) 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 Stand Out (Preferred Qualifications)

• PhD in Engineering, Operations Research, Economics or related field.
• Knowledge of mathematical optimization methods, including stochastic optimization.
• Previous experience deploying ML and/or deep learning models for forecasting to support battery operation.
• Previous experience in power markets forecasting.

Benefits

Base Pay Range: $190,000 - $230,000

Benefits and Employee Perks:

• Competitive compensation and equity grant at a high‑growth start‑up
• Comprehensive benefits package including medical, dental and vision insurance, and 401(k)
• Flexible hours and unlimited PTO
• Diverse and inclusive working environment

Equal Opportunity

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.