Wharton Analytics Fellows

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 analytics.


Analytics Fellows
Acceptance Rate
Projects per Semester
Weeks per project

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.

Featured Partners

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Read About Past Projects

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Keeping Viewers Glued to Their Seats at the 2021 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.
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Students Offer Sweet Solutions to Data Problems at the 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 Wharton Analytics Accelerator, presented by Wharton Customer Analytics (WCA).
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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 Wharton Analytics Accelerator.
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Apply classroom knowledge in a real-world context

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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

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.

Analytics Accelerator

Hosted by Wharton Customer Analytics, the 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. To learn more about the projects, visit WCA’s website.

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
Applications open at the beginning of each semester.

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.


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.


We identified drivers of employee attrition and provided recommendations to improve corporate diversity.


We leveraged performance data to unlock career path insights and kickstart the SEC’s People Analytics practice.

Get Your Company Involved

Interested in working with our data science teams? Reach out to our Wharton partners to inquire about partnering with us.

Wharton Customer Analytics

Customer Analytics

Helping companies understand how to better monetize the individual-level customer data through the development and application of new predictive models.

Wharton People Analytics

People Analytics

Advancing the practice of people analytics and evidence-based management to help individuals and organizations

Sports Analytics and Business Initiative

Applying data-driven decision-making to find new understanding of the evolving sports business industry.

Wharton Analytics Fellows Board

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Zach Bradlow, W'22

Hey, I’m Zach and I am a senior in Wharton studying Finance and Business Analytics with minors in Data Science and Computer Science. I spent my first two years at Penn trying to navigate a path to balance my quantitative love for numbers with my qualitative passion for sports into real-world opportunities; as a junior, I was so happy that I finally found that with Wharton Analytics Fellows. I have worked on two incredible sports projects in the past year: leading a project to optimize roster construction for an NFL team and working with an MLB front office to exploit patterns within a certain position group. Personally, I am really interested in working in the data science field, which I did this past summer interning on an investment research team at a growth equity firm. My hobbies include playing or watching any sport, (ideally) winning strategy board games, being a Penn breakfast sandwich food truck expert, and binging reality television. Happy to answer any questions!

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Ashley Clarke, W'23

My name is Ashley Clarke, and I am a junior at Wharton concentrating in Finance and Business Analytics. I joined Wharton Analytics Fellows during my first semester at Penn. Before college, I had minimal data analytics knowledge. Now, I have had the opportunity to work on three Wharton Analytics Accelerators. These projects taught me how to identify key customer segments using k-means clustering, conduct sentiment analysis on text data, predict a customer’s lifetime value, and countless other skills. Wharton Customer Analytics Initiative and Wharton Analytics Fellows did a great job simplifying and explaining complex data science topics. Currently, I am interested in integrating data science with finance, and I am spending my summer working in investment banking. In my future career, I hope to combine business and data science to solve real-world problems. In my free time, I like to hang out with friends, watch reality tv, try new restaurants, run by the river, and bake. If you have any questions, please feel free to reach out to me!

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Paul de La Borde, W'23

I’m Paul, and I’m a junior studying Business Analytics at Wharton. I’ve been with WAF since the fall of my freshman year, and it’s been a great experience that helped me develop my passion for data science. Through WAF, I’ve worked with clients such as Philadelphia’s Barnes Foundation and Lidl USA. I’m interested in the application of data science to any field, and I spent my sophomore summer interning in equity research. Outside of class, I enjoy rock climbing, reading, and cooking. I hope to see you in a WAF project soon!

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Hassan Hammoud, W'23

Hassan Hammoud is a junior studying Finance and Statistics at the Wharton School and pursuing a Master’s Degree in Data Science from the School of Engineering. I was first drawn into the world of analytics as a freshman when I joined the Wharton Analytics Fellows. Since then, I’ve been able to work on amazing projects, from predicting user purchasing behavior using k-NN to estimating customer CLV and longevity. Right now, I’m interested in exploring how to apply my data science skills in the world of finance, and I’ll be spending next summer on a trading floor in pursuit of that goal. In my free time, I love reading, watching anime, skating and hanging with friends, and playing pretty much any sport. Feel free to reach out if you have any questions about the program!