Broaden your analytics skillset through a semester-long experiential learning project and work with actual companies using real-world datasets
Benefits
Important Dates
Students must be able to commit a minimum of 10 hours a week for 8 weeks.
Selected students will have the opportunity to work directly with leading companies to solve real business challenges using the latest advances in machine learning and AI.
Thank you for your interest. Applications for Fall 2025 are closed.
Fall 2025 AI & Analytics Accelerator Projects
Agentic AI Workforce Impact
Project Details
Accenture aims to examine how the adoption of agentic AI is reshaping workforce demand, job roles, and skill requirements across industries.
Client Insights and Engagement
Project Details
Penn Vet aims to identify patterns in client satisfaction, loyalty, and giving potential to enable smarter segmentation, more timely and personalized solicitations, and targeted marketing strategies.
Pharmaceutical Forecasting and Market Impact
Project Details
RxSense aims to forecast pharmaceutical utilization and pricing trends to help clients anticipate the impact of new drug launches, generic transitions, and broader category shifts.
Data-Driven Rate Optimization
Project Details
Shiftkey’s first project will develop a data-driven model to recommend optimal base rates for new facilities by leveraging regional benchmarks, historical shift fill rates, and specialty-specific demand patterns.
Dynamic Pricing Intelligence
Project Details
Shiftkey’s second project focuses on developing intelligent pricing tools to enhance shift fulfillment and optimize marketplace efficiency.
How it Works
Who Is Eligible?
Penn and Wharton undergraduate and graduate students who show a demonstrated interest in analytics and possess relevant skills ranging from project management, to client relations, to technical expertise. Technical skills are not required but are a plus.
Apply
Submit your application through a highly competitive selection process to become a Wharton Analytics Fellow and get assigned to a company based on your skillset and their needs.
Launch
Kick off the project, meet with your assigned company, and discuss their real-world business challenge.
Analyze
Working closely with a Wharton mentor, analyze the dataset using programming languages and tools of your choice (i.e., Python, SQL) and create a statistical model that helps to solve the business challenge.
Present
Share your findings and recommendations with your company at the AI & Analytics Accelerator Summit.
Role Requirements
Business Lead
Business Leads are responsible for leading and managing the project team, coordinating with clients, and managing the finer details of the engagement. They are usually MBAs or upperclassmen and often have extensive work and leadership experience in business and consulting.
Technical Lead
Technical Leads are data science experts with high-level programming skills who are responsible for the technical aspects of the projects. They build the most complex models and mentor analysts throughout the project. Technical Leads are usually PhD or MSE students with extensive industry experience.
Senior Analyst
Senior Analysts are top undergraduates with advanced skills in programming, statistics, and modeling. They usually have high-level coursework in the CIS and STAT departments under their belt in addition to significant internship and project experience.
Junior Analyst
Junior Analysts typically have intermediate data science skills at roughly the level of STAT 102, STAT 477, and/or WUDAC’s Analytics 101 and 201 courses. They are notable for their willingness to learn and work hard, and many of them progress into leadership roles within WAF in later semesters.
“Having the opportunity to work with real datasets, I was able to gain a deeper understanding of many of the statistical concepts I had learned in my coursework. After working on three AI & Analytics Accelerators, I feel confident in my ability to tackle a real-world, unstructured, data science problem.”
– Ashley Clarke, W’23
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