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Quantitative Development Intern

Job in Durham, Durham County, North Carolina, 27703, USA
Listing for: Cypress Creek Renewables
Full Time, Part Time, Apprenticeship/Internship position
Listed on 2026-06-17
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst, Data Science Manager, Data Scientist
Salary/Wage Range or Industry Benchmark: 25 USD Hourly USD 25.00 HOUR
Job Description & How to Apply Below

The Company

Cypress Creek Renewables is powering a sustainable future, one project at a time. We develop, finance, own and operate utility-scale and distributed solar and storage projects across the country. Fostering a diverse group of innovative thinkers from all backgrounds, Cypress people are drawn to work in a purpose-driven organization. We hope you will join us.

Overview

The Revenue Team at Cypress Creek is responsible for the multi-pronged revenue strategy and comprehensive optimization and risk management for the Company’s development pipeline and operating portfolio of solar and storage projects. The Team is responsible for customer offtake relationships and strives to deliver innovative products that meet their needs in the dynamic renewable energy landscape.

The Revenue Team is seeking undergrad/graduate candidates for a 10–12-week, paid internship in one of our office locations. We are looking for rising seniors, who want to spend the summer learning the ins and outs of the current US solar + storage landscape, as well as hone your energy market and analytical skills in the context of working on analytics applications and dashboards.

The Revenue Team has a strong desire to develop the intern who joins our team, with the hope of this opportunity leading to a full-time offer upon graduation.

Some sample projects you may work on include:

  • Supporting development of software applications and deployment pipelines for product ionizing dashboards.
  • Building solutions to visualize revenue data and creating compelling narratives to enable data driven decision making, for business and operations teams.
  • Supporting data pipelines and warehousing from ingestion to consumption, for time series and interval data.
Qualifications
  • Must be a rising senior (you are currently a junior in college, and after this summer will be going into your senior year) or in grad school.
  • Prefer computer science, statistics or software application development or coursework (include examples in cover letter or resume).
  • Must have intermediate Excel and PowerPoint skills (include examples in cover letter or resume).
  • Strong programming experience in Python, particularly for data processing and ML workflows (e.g., pytorch, Tensor Flow).
  • Familiarity with database management (SQL).
  • Familiarity with cloud platforms/containerization is nice to have.
  • Familiarity in enterprise software development, big data analytics and application development (SDLC).
  • Ideally have a strong desire to work in clean energy / clean tech post college.
In the Cover Letter, please address the following question:
  • Please discuss your interest in renewables and how you have taken steps to become more involved in (or deepen your understanding of) the industry during the past few years.
  • Elaborate any software development experience you have from full time or part time projects that you have done.
Locations

The preferred location for this role is for Chicago, IL or Durham, NC. Additionally, we are on a hybrid schedule 3/week.

Compensation

The hourly rate for our undergraduate internships is $25/hr compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location.

EEO Statement

Cypress Creek Renewables is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. We are committed to providing a workplace that is inclusive and values diversity, and we encourage candidates from all backgrounds to apply.

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