Purpose/Objective of the

Role:

The Data Lab is seeking two motivated students to assist with a real-world analytics project for a water utility company. This position places a strong emphasis on research, specifically identifying the right datasets and determining which factors most significantly influence model performance in the context of utility management and resource optimization. The successful candidates will work independently to extract insights and build predictive models that could have tangible industry impact.

Tasks & Responsibilities:

Data Discovery & Research:

Investigate potential data sources to determine the most suitable data for specific research problems related to water utility operations.

Data Exploration & Analysis:

Perform Exploratory Data Analysis (EDA) to understand data structure.

Feature Selection:

Analyze data to identify key variables and determine which factors influence the model's accuracy.

Model Building:

Design, implement, and validate predictive models using appropriate machine learning algorithms.

Documentation:

Clearly document all research methods, data sources, and results for future reference.

Qualifications/Skills:

Education:

Currently enrolled as an undergraduate major in Data Analytics, Computer Science or Mathematics.

Coursework:

Successful completion of CS 300: Data Mining and Machine Learning (or equivalent coursework/experience).

Technical Skills:

Experience with Python-based data science libraries (e.g., NumPy, pandas, scikit-learn) is preferred.

Soft Skills:

Ability to work independently, manage time effectively, and document work clearly.

Potential Future Career Benefits:

Industry Application:

Apply theoretical knowledge to a live industry project with a water utility company, bridging the gap between classroom learning and real-world application.

End-to-End Data Science Skills:

Gain proficiency in the full data lifecycle, from data discovery and cleaning to feature selection and model building.

Portfolio Building:

Generate tangible results and research experience that can be discussed in future job interviews.

Mentorship:

Work directly with faculty to refine your technical and research methodologies.

NOTE:

Employment sponsorship is not available for this position. Applicants must be currently authorized to work in the

United StatesApplication Instructions:

Complete the ADP application by selecting "Apply" button and answer all questions.

Supervisor:

Mehwish AbbasiCommitment:

5-8 hours per week

Term:

Fall 2026 only