Are you looking for an engaging career in the clean energy market? Do you want to work with a team of smart, passionate people changing the future of energy both financially and environmentally? Is data science your passion? If so, let’s connect!
Position Overview
The energy transition is, at its core, a data and architecture problem. Resurety is looking for a Senior Data Analyst to join our Power Markets team and contribute to the evolution of our price and carbon emission engine.
In this role, you will operate at the intersection of research, engineering and product, supporting the strategy that helps the world’s largest clean energy buyers, sellers, and investors navigate a zero-carbon future. You will work alongside power market experts to increase the accuracy and commercial value of our forecasts, helping to build a scalable platform that defines how the market understands clean energy value. You will advance Resurety’s mission by transforming market research into scalable, high-fidelity forecasting tools, ensuring every insight is communicated with clarity and rigor through operational excellence.
Key Responsibilities
- Support Model Expansion: Assist in the development and testing of REsurety’s fundamental and statistical power price models, helping to maintain the logic that drives our software products.
- Navigate Market Complexity: Assist in managing the lifecycle of power market models, ensuring they stay up-to-date with shifting regulatory landscapes, evolving ISO/RTO market rules, and changing grid fundamentals.
- Maintain Data Integrity: Support the integration of "Weather-Smart" data inputs and assumptions, ensuring our forecasts meet industry standards for accuracy through careful calibration.
- Coordinate with Cross-Functional Teams: Work alongside research, engineering, and product teams with supervision to help transition technical research into scalable, modern modeling platforms.
- Support Stakeholder Communication: Help prepare model outputs and visualizations for internal and external stakeholders, learning to translate complex data into clear, actionable insights.
- Ensure Quality and Accuracy: Execute rigorous quality assurance processes and validate model results to ensure all outputs are accurate, reliable, and provide clear value to our customers.
Required Experience & QualificationsÂ
- 1- 4+ years of experience with power market fundamentals modeling software - e.g., PSO, PLEXOS, PROMOD, or equivalent frameworks..
- Technical Proficiency: Experience using a programming language (Python, R, or SQL) to manipulate, analyze, and visualize data.
- Education: Bachelor’s or Graduate degree in a technical field such as Economics, Engineering, Mathematics, or Statistics.
- Market Knowledge: A strong understanding of the functioning of one or more North American wholesale electricity markets (CAISO, NYISO, ISO-NE, PJM, SPP, MISO, ERCOT).
- Communication: Excellent teamwork and presentation skills, with the ability to help bridge the gap between complex model outputs and commercial decision-making.
- Work in the Boston office three days per week - We are a hybrid office - In the office on Mondays, Tuesdays, and Thursdays. Remote on Wednesdays and Fridays (unless you want to work in the Boston office on those days).
Preferred Qualifications
- Experience with machine learning in an applied setting.
- Experience with capacity expansion modeling.
- Experience with fundamentals modeling, specifically in SPP, MISO, or CAISO.
- A passion for driving the adoption of clean energy.
Compensation, Benefits & Location
- The base compensation range for this position is $81,600 - $95,000.Â
- Actual starting pay is determined by a number of factors, including relevant skills, qualifications, and experience. This range does not include annual bonus, equity-based incentives, and benefits.
- Benefits information can be found at - https://resurety.com/about/careers/
- Boston Office Location - 40 Water Street, 9th Floor, Boston, Massachusetts
Learn more about working at REsurety and our benefits information on our Careers page.
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