Data Scientist II or III

E Source

2d•$85,000 - $130,000•Remote

About The Position

At E Source, we help utilities make sense of complexity in a rapidly changing landscape, and we're looking for a Data Scientist to help shape how that impact shows up in the world. E Source is a research, data/analytics, and technology focused professional services firm focused exclusively on the utility industry in the US and Canada. We help utilities target and serve their customers more effectively, enhance and optimize their grid, and leverage operating best practices and technologies to manage their business more effectively. Headquartered in Texas, we have 450+ employees across the US and Canada. Learn more at www.esource.com As a Data Scientist, you'll leverage your academic training, applied experience, and passion for data science to deploy a range of econometric, statistical, and predictive analytic methods in support of our energy utility clients' customer programs teams. This role is ideal for someone who is equally comfortable building a rigorous model and explaining what it means to a non-technical audience.

Requirements

Hold an advanced degree in economics, statistics, data science, quantitative social science, or another quantitative field (a bachelor's degree plus industry experience will be considered).
Have three or more years of experience in a data science or analytics-related role.
Have expertise with R, Python, SQL, or other programming languages to merge, clean, and model large and complex data sets.

Nice To Haves

Have experience with version control software, such as Git, and collaborative code development.
Have experience with Databricks or Spark.
Have coursework or applied experience in the energy industry, including impact evaluation of energy efficiency, demand response, and/or distributed energy resources programs and initiatives.

Responsibilities

Turn data into insight, analyzing why things happened and predicting what could happen in alternative scenarios.
Develop, validate, and apply econometric and machine learning models to answer client research questions.
Conduct data exploration and evaluate data sufficiency for analysis and modeling.
Describe complex data and modeling concepts in writing and presentation formats to a wide audience, using data to inform critical client decisions.
Exhibit critical thinking and curiosity, including considering how your technical work fits within the larger context of the project, the client, and our industry.
Conduct quality control of your work, apply effective practices to minimize errors, and participate in the peer code review process to ensure high-quality deliverables.