StubHub’s Rockstar Summer Interns
By Adam Ware, Senior HR Business Partner
Published in
10 min readAug 8, 2019
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I can say with full confidence that StubHub has the best summer interns in the industry.
Our interns are driven, courageous, and inventive. They work across many departments at StubHub, including finance, marketing, and communications. A majority of our interns work on teams within Product & Technology. They have a tireless work ethic. They soak up as much experience and wisdom as they can get throughout their three months at StubHub.
The group of 20 is a diverse mix of college, grad school and PhD students who hail from a variety of disciplines: computer science, data science, business, software engineering, design, informatics, applied mathematics and economics.
It’s a competitive job landscape out there, with a lot of fantastic opportunities in reach for this talented group. We’re very lucky they chose StubHub for their intern experience.
Our interns come to StubHub for the real hands-on stuff — not to work on fringe projects just for the sake of “work experience.” They are placed on important projects that will eventually go live on our platforms in front of their very eyes.
They are like our customers: they love concerts, festivals, sporting events, theater — basically any and all live events they can experience.
This summer, many of our interns have been collaborating with Product & Technology teams from across the globe to create products and features that will live on our platforms and make an impact on our overall business.
They’ve seized every opportunity to engage with Sukhinder Singh Cassidy and Arnie Katz, the President and Chief Product & Technology Officer, respectively, to learn firsthand how a multi-billion dollar business is run.
Believe me, it’s a fast and furious three months for these interns. One moment they’re stepping into our offices for the very first time, with a project plan in hand, not knowing quite how StubHub, or maybe any office, operates. The next moment they’re delivering something that’s meaningful for our company and our customers. And before they know it, they’re presenting their work to our senior leaders. They’re given autonomy and a sense of ownership — and have the ability to define the direction of an entire product. StubHub interns commit to a 40-hour work week and get to attend at least one live experience each week.
But don’t take my word for it: Here are a few members from our 2019 StubHub Product & Technology intern class of rock stars who have been killing it for us all summer.
A Place to Make an Impact
Q: What attracted you to StubHub?
- Sai Ranganathan, Software Engineer Intern (University of Washington, Data Science Major): StubHub was a place where I felt that I could make an impact, even as an intern. It is a relatively small company where I would be able to pick projects that I am passionate about.
- Rudra Gandhi, Data Engineering intern, (San Jose State University, Mathematics and Computer Science Major): As a company, I thought that StubHub is an interactive platform for its audiences and accepts feedback very nicely.
- Keshuv Bagaria, Data Engineering intern (San Jose State University, Software Engineering Major): I am a fan of the product and I always wanted to work for a company that was so invested in bringing the joy of watching live sports, theatre and concerts.
- James Thygesen, Product Manager intern for International Growth Team (Brown University, Applied Mathematics/Economics Major): StubHub is a consumer-facing product that I had a lot of experience using prior to joining the company. I could tell from my interviews that the people who work here and the culture that they have created aligned with what I want in a workplace.
- Camila Metello, Technical Product Management intern, Data Engineering Team (Massachusetts Institute of Technology, MBA Candidate): StubHub’s mission and importance in the market were definitely attractive to me. But besides that, one key aspect was that I would be working as a data Product Manager (PM), dealing with machine learning algorithms, and there was no other place I came across that offered such a unique experience for an internship.
- Pooja Janagal Nagaraja, Data Science intern (UCLA, Master’s in Computer Science): In just a few weeks, I have not only learned a lot of new concepts but also have been able to implement them and explain their work to others. All my team members are cooperative and are ready to assist me and offer me guidance at any time.
A Real Job
Q: Does this feel like an internship or a full-time job?
- Ranganathan: It feels more like a real job due to me being able to make an impact while still being an intern. I get to do real work.
- Bagaria: I worked on a project that is crucial for the company. That built a sense of belonging and importance in the company and thereby, made me feel like I was in an actual job rather than an internship. Moreover, I had to talk to employees, enlist their help, and get them to work together on the project.
- Metello: I can honestly say this internship feels like a “real” job. I truly believe in the relevance of the projects I am working in and I am able to interact with many areas of the company. I never feel any sort of discrimination just because I am an intern. I receive the same amount of respect as any other team member. My mentor and my manager ensure that they give me enough freedom to express my opinions. My meetings with my manager involve both of us brainstorming ideas together. He’s not just handing me out a set of instructions for me to follow blindly.
Q: What project are you working on?
- Gandhi: I am working on two projects. One of the projects is to have the data that comes in 24 hours to come in 2-to-5 mins. We want to have live-streaming data for the hit traffic. The second project I am working on is for the marketing analytics team. We want to understand how customer touchpoints, like mobile push notifications, impact user behavior.
- Bagaria: I’m working on two projects: Working on implementing a pipeline to bring real time hit traffic data to GCP. The second is working on a Marketing Analytics project in which we are doing AB testing to help understand the impact of push notifications.
- Thygesen: For my team, I’m working on the event page redesign for some of our more popular international domains. For my intern project, I am working on the UGC feature where users can upload photos/provide feedback about the seating experience that will be displayed in the buy flow.
- Nagaraja: Time series forecasting for different metrics such as GMS, conversion rate and average order value.
Q: What tech challenges have you encountered in your projects?
- Gandhi: In the livestream project, we are addressing the problem of data that comes in a day later. We want it to come faster and in real time — like 2-to-5 minutes. For the second project, we are examining the impact of all customer touchpoints in the mobile app, specifically mobile push notifications.
- Bagaria: The tech challenge was that currently we get hourly reports from Adobe about the traffic on our website. Our challenge was to get that data in real time and insert it into GCP. Currently, the hourly data goes into Oracle and then another script lifts it into GCP. This script only runs once a day — so the traffic data is available to be analyzed every 24 hours. Our job was to build a pipeline that would enable that data to be analyzed in real time.
- Thygesen: For the international project, there is a challenge of addressing the inconsistencies in some of the legal requirements and certain features that we display on our event page. There isn’t a way to automate this since its landscape is relatively fluid, so we need to individually determine and execute on the specifics of each domain.
- Nagaraja: Currently, the available models for time series prediction do not support a range of options. My project, when fully completed, will provide a set of models with which you can predict future values of GMS, conversion rate and average order value for a given genre, performer or event. It will be a one-stop solution for metric prediction and can be used by various departments.
Q: What tech solutions have you employed for your project(s)?
- Ranganathan: We are using technical solutions that include React JS and design libraries such as Ant Design along with Google Cloud Platform Vision API for possible image processing and FireBase, which is a Google Storage system. We are creating a tool that will be used in mWeb and we are building this using the React JS framework, which will then be easily integrable into the new modernized layout of the StubHub website.
- Gandhi: For the livestream project we are using, adobe, written new code and used Google Cloud Platform to help solve this issue. For the second project, we have been testing data and comparing it with different platforms. In the livestream project, we have used Apache Beam to connect to the API that Adobe has given us. We have created two pipelines: one to connect to the API URL, and the other to read from PUBSUB to write into Big Query. After we have done this, we create a table on big query for the data to be transformed into columns and rows. Also, we have used Dataflow to deploy our pipelines there. After this, the data will be transformed into the Big Query table and will keep updating with new data.
- Bagaria: We used Java, Apache Beam, Cloud Dataflow, Cloud PubSub, and Cloud Big Query to solve the problem. We created two data pipelines to accomplish our goal. The first pipeline connects to the Adobe API and opens a connection to the livestream. Then, our pipeline, which is staged on Cloud Dataflow, uses the Apache Beam framework to read this data that comes in as a stream from the Adobe API and then puts that data into Cloud PubSub. The second pipeline reads the data from Cloud PubSub and then, using Apache Beam, transforms that data before putting it into Big Query. This pipeline is also staged on dataflow. Cloud Dataflow helps scaling as we process streaming data and Cloud PubSub helps in concurrency and de-coupling the two pipelines. The two pipelines are completely decoupled from each other.
- Thygesen: We used Optimizely to run A/B test campaigns. There is a lot of work to be done on the display side in regard to the different forms of messaging that we display on different event page domains. Additionally, there was a lot of intricate functionality relating to the mapping system.
- Nagaraja: I am making use of Recurrent Neural Networks for time series forecasting. I am building a number of RNN models to support different combinations. I have never worked with RNN in so much depth before, so this is really exciting for me.
Leave work every day knowing you did your best
Q: Have you had face-to-face time with StubHub’s leadership team?
- Metello: I was blown away by the talent of our leadership, which I got to meet during the “Brown Bags.” I was especially impressed by Sukhinder’s ability to lead. When she speaks, it is clear what a passionate leader she is and how much she cares about StubHub and its employees.
- Bagaria: Moreover, I had a good conversation with Arnie Katz (Chief Product & Technology Officer) in which I got a chance to explain my project and discuss with him the need and validity of my project.
- Thygesen: Sukhinder was very nice and engaging when I spoke with her. She’s a very impressive executive. Arnie and Olivier (CPTO and CMO, respectively) were similar in that they were very engaging and seemed curious about the work that I was doing, which was very encouraging.
- Nagaraja: We were given the opportunity to have lunch with Sukhinder and ask her any questions. She gave us a lot of advice on how to be on the top of your game right at the beginning of your career. One of the pieces of advice she gave was, “Leave work every day knowing you did your best and that you cannot wait to do more of it tomorrow”. This is something that will stick with me.
Q: When all is said and done, has your internship encouraged you to pursue a career in tech or has it scared you away?
- Ranganathan: The internship has been a very meaningful experience and has helped me gain real industry experience that I can take with me for the rest of my career. I definitely love working at StubHub and would love to come back next year and pursue a full-time job here as a software engineer.
- Gandhi: Before coming into this internship, I wanted to be a professor after I graduated. However, after working and using such high-tech tools, I don’t think I would be able to do this if I am teaching. After graduation, I want to work as an engineer or an analyst to continue using these tools and to learn everyday while on the job. Not only do we just learn things here, but we also get to implement and use what we have learned. Each day is a new experience and working at StubHub has made me realize what I want to do after I graduate.
- Bagaria: The internship has convinced me to pursue a professional career in tech after graduating instead of going straight into a Master’s program. Moreover, I have realized that when I do a Master’s, I would love to do it in Data Science or machine Learning. It has been one of the most valuable experiences of my life because every day I learnt something new about myself and the field of coding.
- Metello: This internship gave me a true PM experience. I have no doubts I want to pursue my career as a PM after I graduate.
- Nagaraja: This is my first Data Science internship and I am so grateful for having learned so much. This is very different from my academic Data Science projects. I deal with real, industry-level data every day and I get to play with it and use it to train my models. I work with a couple of highly-experienced data scientists who have really cool insights and are always ready to share their knowledge with me.
