Intern - Year Round (Data Scientist)

The Data Scientist Intern supports advanced analytics and predictive modeling that informs member growth, market potential, and branch network strategy. This role applies statistical, machine learning, and spatial analytics techniques to large enterprise datasets to identify patterns, forecast demand, and generate actionable insights for strategic planning.
The intern works closely with principal data scientists and geospatial analysts to develop models and analytical frameworks that enhance location intelligence, behavioral analytics, member insights, and market opportunity assessment.

****A requirement of this position is you must be currently enrolled in college level courses or a degree-seeking program throughout the duration of the internship. Please upload your transcripts by adding them to the “Intern Proof of Enrollment” section of the application.

• Develop and evaluate predictive models to estimate member growth, market potential, and branch demand
• Apply statistical and machine learning techniques to identify drivers of member acquisition and engagement, member and market behavior, and value of a market
• Support model validation, performance assessment, and documentation
• Analyze member demographic, behavioral, and geographic data to generate market insights
• Contribute to market sizing, segmentation, and opportunity analyses
• Support development of demand and growth forecasting methodologies
• Collaborate with GIS analysts to incorporate geographic features into predictive models
• Engineer spatial and demographic features for modeling and analysis
• Support analyses linking member behavior and geography to branch strategy
• Extract, clean, and integrate large datasets from enterprise data platforms (SQL, Databricks, etc.)
• Build reproducible data pipelines and modeling datasets
• Ensure data quality and documentation for analytical workflows
• Summarize analytical findings and model outputs for technical and business audiences
• Contribute to presentations, visualizations, and analytical documentation
• Translate quantitative results into clear business implications
 

• Currently pursuing a graduate degree (MS or PhD) in Data Science, Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related quantitative field
• Strong foundation in statistics, probability, and predictive modeling
• Proficiency in Python or R for data analysis and modeling
• Experience working with large datasets using SQL or similar tools
• Demonstrated ability to structure and analyze complex, real-world data problems
• Strong analytical reasoning and problem-solving skills
• Ability to communicate technical concepts clearly
• Curiosity, initiative, and ability to learn quickly in an applied business environment

Desired:
• Experience with machine learning or predictive modeling projects
• Experience with spatial, geographic, or demographic data
• Familiarity with ETL processes and data preparation workflows
• Experience with Alteryx and/or ArcGIS
• Experience with feature engineering and model evaluation techniques
• Experience with Databricks, Spark, or cloud data environments
• Interest in applied analytics for market strategy, location intelligence, or growth analytics