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.

   Spring 2022 Analytics Accelerator Recap – Kimmel Cultural Center

Fall 2023 – 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:

August 29 - September 10

Student Application Open

September 29

Project Launch Meetings

December 1

Analytics Accelerator Summit

Fall 2023 Projects

Align is seeking out the assistance of Analytics at Wharton to understand key customer attributes and behaviors for optimal growth program candidacy and success across program tiers.

In collaboration with Analytics at Wharton, IKEA wants to focus on their e-commerce platform to better understand the behaviors of their website visitors to be able to predict future journeys and actions, such as adding items to their cart, viewing products, making a purchase, and more.

Online marketplace TaskRabbit matches freelance labor with local demand. They hope to quantify the value of partnering with IKEA, including investigations into business growth by geographic region, customer satisfaction, and value of customers who were introduced to TaskRabbit through IKEA.

Leading real estate marketplace Zillow is partnering with Analytics at Wharton to create two predictive models, factoring in internal controls and external societal influences, to forecast website visits and Zillow Home Loan applications.


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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

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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

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.

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
The Spring Application is closed.

Featured Partners

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Electronic Arts Logo
FOX Entertainment Logo
McDonald's Logo
Moelis Logo

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.
Read article >>

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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).
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 Wharton Analytics Accelerator.
Read article »

Wharton Analytics Fellows Board


Mohul Aggarwal, W'25

Hi everyone! My name is Mohul Aggarwal, and I’m a sophomore studying Statistics and Finance. This is my third semester in WAF, and I’ve been involved in two projects–WPA Happiness Research and MLS. In my spare time, I’m involved in fusion dance through Penn Dhamaka and love weight-lifting. I’m super excited to be working alongside the WAF Board to bring you all the best experience possible!

Contact Mohul at rcmand@wharton.upenn.edu


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Kyle Laio, SAS'25

Hi! My name is Kyle Liao and I am a junior in the College studying computer science and biology and submatriculating in data science. This is my third semester with WAF, and I really enjoyed working with Petco last spring. On campus, I have been involved with the Wang Genomics Lab and the Wharton Undergraduate Healthcare Club. In my free time I enjoy volleyball, thrifting, and playing board games. I am super excited to work alongside the rest of WAF board to make this semester a great experience for everyone!

Contact Kyle at kyleliao@upenn.edu



Rishabh Mandayam, W'25

Hey everyone! My name is Rishabh Mandayam and I am a sophomore in the M&T program studying CS, Finance, and Statistics. This will be my third semester in WAF. I was previously on the FOX team doing an analysis of blockchain transactions and on the Align team building predictive models for their marketing campaigns. Outside of WAF, I am a member of Penn Quant’s Strategy development team and a board member of the Penn Central Banking Club. I also am a member of Penn Judo and play intramural soccer in my free time! I look forward to working with everyone this semester.

Contact Rishabh at rcmand@wharton.upenn.edu



Annie Wang, W'25

Hi everyone! I’m Annie and I’m a sophomore in Wharton and the College interested in business analytics, math, and computer science. This is my fourth semester in WAF and I’ve been part of the Zillow and IKEA project. In addition to WAF, I’m also involved in WUREC, WiCS, and Penn Chamber. I’m so excited to work with everyone and look forward to making WAF an amazing experience alongside the board!

Contact Annie at yfanwang@wharton.upenn.edu



Brian Williams, SEAS'25

Hey everyone! I’m Brian Williams, a junior in the School of Engineering and Applied Science studying Computer Science with minors in Engineering Entrepreneurship and Korean. This will be my third semester with WAF, and my past projects include Master Kong and Fox Entertainment. Besides WAF, I’m also involved with Hack4Impact, and enjoy cooking as well as spending time outdoors. I’m looking forward to working with you all!

Contact Brian at bewill@upenn.edu



Jon Wu, SEAS'25

Hi everyone! I’m Jon Wu, a junior in the School of Engineering & Applied Science studying Systems Engineering and submatriculating in Data Science. As WAF’s Vice President of Social, I hope to bring together the WAF community so the organization can thrive and better serve its clients. My previous projects on WAF include Teach For America, McDonald’s, and Master Kong. In addition to WAF, I’m involved with the Engineering Deans’ Advisory Board and am passionate about utilizing advanced analytical methods to solve business and management problems.

Contact Jon at jonawu@upenn.edu



Joanna Yang, W'24

Hello everyone! I’m Joanna Yang, a senior in Wharton studying Statistics and Finance, minoring in Computer Science, and submatriculating in Data Science. I’m originally from San Jose, CA. This will be my seventh semester in WAF and I’ve been on four projects– RBI, Fox Entertainment, Master Kong, and McDonald’s. On campus, I’ve also been involved in MUSE Consulting, intramural volleyball, and recently, rock climbing! I’m super excited to meet you all and work with you– please reach out to me if you have any questions about WAF or anything at all!

Contact Joanna at  joannay@wharton.upenn.edu


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

AI & Analytics for Business

Applying artificial intelligence and advanced analytics to transform and innovate business enterprises and support AI applications within academic disciplines that include human-AI collaboration.

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.

Selected Projects

Impressionist Painting

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.