Who Are We?
Looking for a job that makes a real difference in our world today and one that you’ll be proud of when you look back in 20, 30 or 40 years? This is it. Clean Power Research® is advancing the energy transformation through cloud software that informs, streamlines and values energy-related decisions and processes for utilities, energy professionals and consumers.
We’re a growing company that counts 10 of the top 10 Fortune 500 utilities and many of the largest renewable energy companies in the U.S. as our customers. We’re focused on expanding our market reach and impact with new software technologies that help solve the energy industry’s hardest problems.
At Clean Power Research, every employee has a seat at the table and an important role
Why Work Here?
- Go from building solutions to being part of the solution
- Join a growing team of software and energy veterans from companies like Microsoft, Amazon, Google, Oracle, General Electric and Pacific Gas & Electric
- Bring your passion and ideas to the table
- Use your creativity to solve hard problems and make tough decisions
- Work in a start-up like environment coupled with the stability and customer base of an established, profitable company
- Realize work-life balance; we like to see our families, friends and pets at night!
- Join a growing company that expects you to grow with us and invests in your growth
Clean Power Research offers competitive compensation and benefits to full-time employees including medical/dental/vision, paid vacation, paid holidays, a bonus plan and 401(k) plan with matching.
What You’ll Be Doing as a Data Scientist
Clean Power Research is seeking an entrepreneurial-minded Data Scientist with the skills and ingenuity to solve complex problems. The Data Scientist will work closely with the Data Science team, researchers, software engineers and product managers to develop and implement data science, machine learning, and statistical methods across our multifaceted, enterprise SaaS platform.
The CPR platform, comprised of our PowerClerk®, WattPlan®, and SolarAnywhere® products, enables utilities and the energy industry to inform, streamline and value energy-related decisions and processes. Across our products, a variety of best-in-class, highly unique datasets are growing every day, from a nationwide database of 1 km resolution solar irradiance data derived from satellite image feeds, to a continuous data feed of customer interest in clean energy technologies.
Clean Power Research is leveraging these datasets to solve new customer problems. The Data Scientist will identify and research additional data sets and will elevate the use of these datasets in new and existing software products, with rigorous application of machine learning fundamentals, from problem definition, data preparation, and validation, to agile prototyping.
This is a great opportunity for long-term growth as the company continues to evolve its services in an increasingly complex, competitive, and global marketplace. The Data Scientist will help decide where and how data science is applied at Clean Power Research to answer meaningful customer problems in the burgeoning clean energy space. A highly motivated and self-driven individual will excel in this role.
Duties and Responsibilities
- Work closely with researchers, software engineers, and product managers across our SaaS platform to define specifications for developing and enhancing applied data science, machine learning, and statistical methods
- Quickly develop machine learning prototypes, apply a procedural framework to assess the performance of a variety of machine learning algorithms, and identify the most suitable approaches
- Process, transform, and experiment with high volumes of data to optimize model accuracy
- Identify new potential data sources to enhance model performance
- Develop and validate high quality machine learning models that will be brought to scale in production by our software engineers
- Identify and evangelize opportunities to leverage data science and machine learning to improve existing products and services and opportunities to develop new ones
- Work closely with researchers to support projects where data science and machine learning expertise is needed
- Communicate with Clean Power Research customers on the details of our machine learning capabilities and performance metrics
- Represent Clean Power Research at industry events and conferences
Who You Are
- Entrepreneurial-minded individual with exceptional enthusiasm for evangelizing and driving the implementation of data science approaches throughout a growing company
- 6+ years of combined education and/or experience in engineering, mathematics, data science, statistics, computer science, or related field
- Experience creating working ML solutions from ideation, validation, and application
- Strong analytical skills and hands-on experience of methodically applying machine learning approaches, from problem definition, to data preparation, to agile prototyping
- Coding skill with Python
- Experience with cloud computing is a plus
- Coding skills for analyzing data and building statistical and machine learning models
- Passion for clean tech, solar energy, and renewables
Pay Range and Benefits
- Base Salary Range: $84,000 to $120,000 annual depending on experience
- Benefits: Performance-Based Bonus, Company Equity Plan
- Additional Benefits: Paid PTO, Sick Time, Holidays, Medical/Dental/Vision/Life and Disability Insurance, 401K, Paternity and Maternity Leave, Commuter Benefits
How to Apply
Click the link below to submit your resume. Please include a cover letter detailing your interest in this position and the renewable energy space along with your resume. Due to the large number of applicants for our positions, we regret that we can only respond to candidates who meet our requirements.
Clean Power Research is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
The company’s employment decisions are based on merit, competence, performance and business needs.