Broaden your analytics skillset through a month-long experiential learning project and work with actual companies using real-world datasets
Benefits
Spring 2025 AI & Analytics Accelerator – 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 actual business challenges using the latest advances in machine learning and AI.
Applications close January 31.
Spring 2025 AI & Analytics Accelerator Projects
Marketing Mix Models (MMMs) with Google
Google aims to focus on enhancing Marketing Mix Models (MMMs) to estimate longer-term effects of advertising by incorporating new response variables, such as brand value indicators like Google search queries. It also aims to create more dynamic, granular MMMs with daily-level updates, providing improved insights and scalability for long-term impact assessment and model implementation.
Leverages AI Technologies to Detect Potential Cases of Fraud, Waste, and Abuse with CenterWell
CenterWell aims to develop a model that leverages AI technologies to detect patterns in our data that may indicate potential cases of fraud, waste, and abuse.
Automate Client Onboarding with RxSense (Red)
RxSense aims to automate client onboarding by developing a template based on historical claims data from past clients, streamlining the process of designing plans for prescription needs. This approach minimizes manual effort, enabling faster, more accurate, and efficient onboarding.
Analyze Pharmaceutical Demand Trends with RxSense (Blue)
RxSense aims to analyze pharmaceutical demand trends, such as the 2023-2024 spike in Ozempic usage, to better forecast pricing and client cost trends. This insight will enable RxSense to optimize pricing strategies and offer cost-saving drug-switching alternatives to members.
Develop an AI tool to Predict Sales Trends with Spencer's Gifts
Spencer’s Gifts seeks to develop an AI tool to predict sales trends for t-shirts and other trendy items by analyzing historical and current data. The tool will provide weekly reports to the Planning Team, highlighting projected changes in sales, including the magnitude, timing, and revenue impact of these shifts.
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.
“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
AI & Analytics Accelerator Case Studies
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Previous Partners
Spring 2024 Student Spotlights
Last spring, the Wharton AI & Analytics Initiative hosted its 12th AI & Analytics Accelerator, an experiential learning opportunity which pairs teams of students from across the University of Pennsylvania with participating companies.
Peggy Pranschke from Petco worked with teams of Wharton and Penn students to leverage machine learning and data analytics to help develop novel solutions for supplementing email marketing campaigns for her company.