DERs Data Scientist I, Solar Programs (Remote -US)

Energy Solutions - USA

11h•Remote

About The Position

Interested in joining a growing company where you will work with talented colleagues, enhance a supportive and energetic culture, and be part of the climate solution? At Energy Solutions, we focus on the big impacts. And we believe that market-based programs can be a powerful force to deliver large-scale energy, carbon, and water-use savings. Since 1995, we’ve harnessed that power to offer proven, performance-based solutions for our utility, government, and institutional customers. We are currently seeking a Data Scientist I, Solar Programs, for the Distributed Energy Resources Team (DERs) to assist with the development of analytical models, dashboards, and data pipelines to provide insights to internal and external stakeholders. Working closely with senior team members, this role will apply statistical techniques and foundational machine learning methods to clean, analyze, and interpret data. They will support data quality efforts, document analyses, and communicate results while continuously building their technical and analytical skills.

Requirements

A bachelor’s degree.
A minimum of 2 years of relevant work experience.
1 year of Python experience, including libraries like pandas, numpy, and scikit-learn.
Experience building basic dashboards or reports using BI tools (Tableau preferred).
Experience developing analytical models or performing structured data analyses using a high-level programming language
Foundational knowledge of descriptive and introductory inferential statistics.
Familiarity with common machine learning techniques and basic understanding of data warehousing concepts and ETL processes.
Ability to work effectively on a team, manage individual work streams, and explain analytical results clearly to various audiences.
A technical test will be required during the interview process.

Nice To Haves

Master’s degree coursework (in progress or completed) in a quantitative field.
Foundational data analytics certifications (e.g., Coursera, edX, DataCamp).
Exposure to R for data cleaning and analysis.
Foundational awareness of version control and collaborative coding practices like Git/GitHub.
Experience supporting analytical projects in academic, internship, or early-career professional settings.

Responsibilities

Execute assigned tasks to assist in the development and maintenance of analytical models, dashboards, and reporting outputs.
Analyze datasets using established statistical techniques and basic machine learning methods to support defined analytical objectives.
Apply foundational modeling approaches, including string‑matching and reconciliation techniques, to structured analysis tasks as directed.
Prepare intermediate analytical outputs (tables, summaries, visualizations) for review and iteration.
Execute data cleaning and transformation in Python or R, following established ETL and data processing workflows.
Draft clear summaries of findings and document data sources, assumptions, and methodologies in accordance with team standards.
Prepare charts, tables and dashboards visualizations to support stakeholder understanding and decision-making.
Support collaboration with internal teams and project stakeholders by gathering requirements and clarifying data needs.
Participate in code reviews, documentation reviews and team knowledge-sharing activities.
Assist with maintaining organized project files, analysis artifacts, and reference documentation.