Intern, Energy Data Science
Dairyland Power Cooperative•La Crosse, WI
•Onsite
About The Position
The Energy Data Science Intern will support strategic decision making by increasing data accessibility, performing statistical analysis, building predictive models, and providing actionable insights. This position advances all DPC’s strategic priorities, but most notably our commitment to financial strength, growth & innovation, and our safety culture.
Requirements
- Currently pursuing either an undergraduate or graduate degree in data science, statistics, mathematics, artificial intelligence, computer science, or another related field.
- Experience using at least one scientific computing language, preferably Python
- Foundational knowledge of data structures, statistical analysis and relational databases
- Strong analytical, problem-solving and organizational skills
- Strong verbal, written and interpersonal communication skills
- Ability to work independently.
Nice To Haves
- Experience with SQL and data modeling
- Experience building data pipelines or integrating APIs
- Familiarity with Microsoft Fabric, AWS or another cloud data platform
- Familiarity with machine learning model development, validation, and deployment
- Experience with Power BI or another data visualization tool
- Experience using Git or another version control system
Responsibilities
- Build, test and document data pipelines that ingest, transform and deliver data for analysis and reporting.
- Assist with integrating APIs, databases, enterprise applications and external data sources into Dairyland Power Cooperative’s cloud-based Lakehouse environment.
- Clean, validate and organize energy and business data to improve reliability and accessibility.
- Perform statistical analysis to identify trends, quantify uncertainty and support business decisions.
- Develop and evaluate machine learning models for defined business applications.
- Support model deployment, validation, performance monitoring and ongoing improvement.
- Translate business questions into quantitative analyses.
- Present findings, assumptions and recommendations clearly to technical and nontechnical audiences.
- Create technical documentation for data sources, pipelines, models and analytical methods.
- Perform other duties as assigned.
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
