The Data Incubator is an intensive eight-week data science bootcamp which trains people with STEM backgrounds to become in-demand data scientists. With an acceptance rate of just 2%, we wanted to find out what the application process is like, and the types of applicants that The Data Incubator accepts. We asked Alyssa Thomas and The Data Incubator admissions team to answer all of our questions about how to successfully get through the application (hint: the project proposal is key!) and interview process.
How long does the Data Incubator application typically take? What are the steps applicants should expect?
The entire application process is spread out over the course of roughly six weeks. After the deadline, initial applications are reviewed and semi-finalists are selected. Semi-finalists must complete the technical challenge portion of the application. From this pool of candidates, finalists are selected and are asked to schedule admissions interviews. Admissions decisions are made after the interviews (which are typically spread out over about two weeks) and applicants are notified of final decisions within about a week of the conclusion of interviews.
What is the technical challenge portion of the application like? Can you give us a sample question?
The technical challenge consists of a programming challenge and a data challenge.
Here is a sample of one of our past challenge questions. We don’t re-use them, but this gives you an idea of what to expect:
A chess knight piece is sitting on the "0" key of a numeric keypad.
The knight makes T jumps to other keys according to its allowable moves (so that from each reachable key it has two or three allowable moves). The knight chooses amongst the allowable moves uniformly at random and keeps track of the running sum SS of keys on which it lands. We are interested in S under the modulo operator.
After T=10T10 moves, what is the expected value of the quantity S mod 10?
How long should the coding challenge take? Is there a time limit?
We give applicants five days to complete the challenge (including project proposal and video submission - more about this below) but the coding challenge itself takes at minimum four hours to complete.
In what programming language should the applicant complete the coding challenge? Does this have to be in Python?
The coding challenge supports several different languages. C/C++, Matlab, Stata, Fortran, Perl, SQL, IDL, Python, VBA, Java, and R will all work.
How should a student who doesn’t have a background in Python prepare for the coding challenge?
The programming challenge can be done in just about any language, the data challenge could be done in SQL, R or possibly several other languages with a bit more work. We encourage everyone to learn Python, but if it isn’t the language you’re most comfortable with at this point there are options!
What goes into the written application?
We require short answers for each of the following:
- Tell us about what makes you excited about data science generally.
- Tell us about what makes you excited about The Data Incubator specifically.
- What would you do if you were not accepted as a Fellow for The Data Incubator?
- Tell us about your industry job search experience so far.
- Anything else? You can write about courses you took, side projects related to data science, or anything that you are passionate about.
We also ask for information about degree status (current/expected), educational background, work experience, programming experience, mathematical/statistical experience, industries of interest, and geographies of interest.
Does Data Incubator require a video submission? What’s the purpose of the video submission?
Applicants submit their video along with the technical challenge. In the video we want you to pitch your project proposal to us, tell us what would make your project unique and worthwhile!
What is the Project Proposal?
Towards the end of the bootcamp, Data Incubator Fellows complete a Capstone Project separate from the weekly mini projects. This Capstone Project can cover any subject you like - and we’ve seen everything from Chicago crime data to using machine learning to categorize Google images. So when you are applying, the project proposal is your chance to tell us what you’d like to work on and why it matters. The best project proposals are the ones that show off your unique perspective and explain the business relevance of the work you’re doing.
What types of backgrounds have successful Data Incubator students had? Does everyone come from a technical background?
We’ve had successful Fellows from almost every academic background. Of course, Physics, Engineering, and Math are popular majors, but we’ve also had Anthropologists, Political Scientists, and Marketing PhDs who were very successful in our program. Most Fellows have been coding for at least a year, but certainly not all of our Fellows came from technical backgrounds.
What are the education requirements for a Data Incubator student?
We require Fellowship applicants to be within a year of completing their Master’s Degree or PhD.
Who conducts Data Incubator interviews? Should applicants expect to be talking with a founder, an instructor, or an alumni?
All of the above! Our founder participates in interviews, as do our instructors (some of whom are Data Incubator Alumni) and our partnerships team.
Is there a technical component to the Data Incubator interview or are you looking for culture fit?
We ask everyone to present their project proposal and answer a few questions about the proposal from other prospective Fellows. We’re looking for the technical ability (and potential) in the project proposals, but also paying attention to interaction with other prospective Fellows in the interview session. Our program is very hands-on and does require a lot of working together, so we’re paying attention to both cultural fit and the way applicants interact with others.
Can you give us a sample of a Data Incubator interview question?
“Why are you transitioning into Data Science?” It sounds simple but it tells us a lot about an applicant’s motivation for entering the program. The program isn’t easy and the most successful Fellows are the ones that are really committed to this field.
How do you evaluate an applicant’s future potential? What qualities are you looking for?
We want each class to bring a variety of different backgrounds and perspectives, so there isn’t any one specific thing we look for. We like to see applicants who have given serious thought to their project proposals though, and we highly value presentation skills and the ability to distil a complex subject into a format anyone can relate to. We also look for Fellows who are very motivated to enter the field of Data Science quickly and make the most of their time in the Data Incubator.
Can applicants do the interview in-person or are all interviews conducted online?
We conduct all of our interviews online.
Are students accepted on a rolling basis?
We don’t do rolling admissions. Fellows are accepted for one of the four sessions we hold throughout the year and will be notified of their acceptance about a month before the session is scheduled to begin.
What is the current acceptance rate at Data Incubator?
Right now it’s a little over 2%, but don’t let that scare you!
Does Data Incubator accept international students? Do international students get student visas/tourist visas to do the program?
We will accept international students, but we do not provide visa sponsorship.
Can rejected applicants reapply to The Data Incubator? If so, how many times?
It is a very competitive admissions process. But several of our most successful Fellows were those who applied more than once, and there isn’t a limit on how many times you are eligible to apply. Often applicants who are not admitted the first time they apply spend the time before the next admissions cycle working on their skills or improving their project proposals, which can make them even stronger candidates the next time they apply.