Energy Data Science Intern: Build Pipelines & Models

dairynet; La Crosse (WI); On-site; USD 36,000 - 47,000; Part time

Job summary

DairyNet Energy Data Science Internship seeks a student to support data accessibility, perform statistical analysis and build predictive models. The role advances strategic priorities like financial strength and innovation while enhancing safety culture.

Responsibilities include pipeline development, API integration, data cleaning and model evaluation, with opportunities to present insights to diverse audiences and document technical methods.

Qualifications

• Currently pursuing either an undergraduate or graduate degree in data science, statistics, mathematics, artificial intelligence, computer science, or another related field.
• Python and data analysis fundamentals required.
• Strong communication and organizational skills.

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 the cloud environment.
• Clean, validate and organize data to improve reliability and accessibility.
• Perform statistical analysis to identify trends and support business decisions.
• Develop and evaluate machine learning models for defined business applications.
• Support model deployment, validation, and monitoring.
• Translate business questions into quantitative analyses.
• Present findings clearly to technical and nontechnical audiences.
• Create technical documentation for data sources, pipelines, models and methods.

Skills

Python

Data structures

Statistical analysis

Analytical skills

Communication skills

Independent work

Education

Pursuing undergraduate or graduate degree in data science / statistics / AI / CS

Tools

SQL

Power BI

Git

AWS

Microsoft Fabric

Job description

DairyNet Energy Data Science Internship seeks a student to support data accessibility, perform statistical analysis and build predictive models. The role advances strategic priorities like financial strength and innovation while enhancing safety culture.

Responsibilities include pipeline development, API integration, data cleaning and model evaluation, with opportunities to present insights to diverse audiences and document technical methods.