The Wharton Analytics Fellows program unites Wharton undergraduates, MBAs, graduate students, and faculty members in the pursuit of a common goal: tackling our clients’ most complex challenges using the power of AI and analytics.
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Wharton Analytics Fellows
Wharton Analytics Fellows is a highly selective fellowship program that allows motivated Wharton undergraduates, MBAs, and graduate students to put their analytics skills to the test in the real world. Fellows consult for our clients on their toughest data science problems, building them predictive models and presenting their findings to senior leadership. Our clients put these models into practice, giving students the opportunity to see their work have a real impact.
For more information, contact whartonanalyticsfellows@wharton.upenn.edu.
AI & Analytics Accelerator
The AI & Analytics Accelerator gives selected students the opportunity to work directly with leading companies to solve actual business challenges using the latest advances in machine learning and AI.
Who is Eligible
Penn and Wharton undergraduate, MBAs, 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.
How to Apply
Spring 2025 applications are open through January 31. Email whartonanalyticsfellows@wharton.upenn.edu with any questions.
Spring 2025 – Important Dates
Students must be able to commit a minimum of 10 hours/week for 8 weeks, and be available on the following dates and times:
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.
Leverage 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.
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.
Benefits
Apply classroom knowledge in a real-world context
Consult for some of the world’s biggest companies on extremely interesting projects
Join a community of some of the best data scientists at the University and improve your skills
Access exclusive recruiting opportunities with top firms in a variety of industries
Wharton Analytics Fellows Board
Aeshon Balasubramanian, SEAS '26
Vice PresidentHey everyone! I’m a junior in SEAS studying Computer Science. I am beginning my sixth semester with WAF, and have enjoyed working as a technical lead and analyst on projects with companies like Hearst, TaskRabbit, and Lowe’s. Outside of WAF, I am a teaching assistant for CIS 5450, Big Data Analytics, and enjoy going to the gym, playing chess, and watching sci-fi movies and TV. I look forward to working with you all this year!
Contact Aeshon at aeshon@seas.upenn.edu
Frank Ma, W '27
Vice PresidentHi! My name is Frank Ma and I am a sophomore studying Finance, Statistics and CIS. This is my third semester in WAF. I was previously involved with a customer segmentation project with Fox Entertainment, and a Credit Default Swap portfolio analysis project with Orchard Global Asset Management. In my free time I enjoy long-distance running and lifting. Looking forward to working with everyone this semester!
Contact Frank at fanghema@wharton.upenn.edu
Andrew Mao, M&T’26
Vice PresidentHey everyone! I’m a junior in the M&T program studying Electrical Engineering and Finance. I’ve been in WAF since freshman year, where I’ve built predictive models for web traffic with Zillow and computer vision for game analysis with Penn Athletics. Outside of WAF, I’m involved with Penn Growth Equity and previously played Penn Men’s Hockey. I’m also working with world-class golf courses in Asia to develop computer vision-based golf technology suites. I look forward to working with everyone this semester!
Contact Andrew at am123@wharton.upenn.edu
Pulkith Paruchuri, M&T '27
Vice PresidentHey! I’m Pulkith Paruchuri, a sophomore in M&T studying Computer Science, Finance, and Math. I’ve been in WAF since freshman fall, where I enjoyed working with IKEA on improving online customer conversion. At Penn, I’m involved in Hack4Impact, MLR, and finance clubs. I enjoy playing volleyball and pickleball, F1, hiking, poker, and Wawa. I look forward to working alongside WAF Board to foster an exciting semester of learning!
Contact Pulkith at pulkitch@wharton.upenn.edu
Allan Zhang, SAS '27
Vice PresidentHi everyone! My name is Allan Zhang, and I’m a sophomore studying Statistics and Mathematics. This is my third semester in WAF, and I’ve previously worked on projects with Dallas Area Rapid Transit and Orchard Global. In my free time, I like playing chess (especially bullet/blitz), solving puzzles, and hiking. I’m looking forward to working with everyone this semester!
Contact Allan at allzhang@sas.upenn.edu
Petco Gains New Insights, Quick Results Through AI & Analytics Accelerator
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.
Read About Past Projects
Keeping Viewers Glued to Their Seats at the 2021 AI & Analytics Accelerator
An MBA and undergraduate student team analyzed data from FOX Entertainment to help inform data-driven promotion strategies for marketing their TV shows.
Read article >>
Students Offer Sweet Solutions to Data Problems at the AI & Analytics Accelerator
How strong is the halo effect when it comes to selling candy and gum? This was among the many questions students set out to answer during the third annual AI & Analytics Accelerator.
Read article >>
How a Penn/Wharton Student Team Is Helping the Barnes Foundation Reach Bigger Audiences
When the Barnes Foundation had questions about its attendance data, a team of Penn students answered through the AI & Analytics Accelerator.
Read article »
Get Your Company Involved
Interested in working with our data science teams? Reach out to our Wharton partners to inquire about partnering with us.
AI at Wharton
Applying AI and advanced analytics to transform and innovate business enterprises within academic disciplines that include human-AI collaboration.
People Analytics
Advancing the practice of people analytics and evidence-based management to help individuals and organizations thrive.
Sports Analytics and Business Initiative
Applying data-driven decision-making to find new understanding of the evolving sports business industry.
Wharton Neuroscience Initiative
Building Better Business through Brain Science.
Selected Projects
Barnes Foundation
We provided the Barnes with a model for predictive analysis, incorporating pricing, revenue projection, visitation and attendance behavior, products, and promotional offers.
Moelis
We designed a Bayesian Graphical Model to understand an activist investor’s success and predict the result of proxy campaigns.
San Francisco Giants
We developed a predictive engine to improve ticket sales forecasting by more than 30%.
EA Games
We drive player engagement and retention by predicting online behaviors and using customer-level data.
L’Oreal
We identified drivers of employee attrition and provided recommendations to improve corporate diversity.
SEC
We leveraged performance data to unlock career path insights and kickstart the SEC’s People Analytics practice.