The Data Incubator

Data Scientist: The Sexiest Job
of the 21st Century
Harvard Business Review

Data Science Fellowship

New York City | San Francisco Bay Area | Boston | Washington DC

The Data Incubator is a Cornell-funded data science training organization. We run a free advanced 8-week fellowship (think data science bootcamp) for PhDs looking to enter industry. A variety of innovative companies partner with The Data Incubator for their hiring and training needs, including LinkedIn, Genentech, Capital One, Pfizer, and many others. The program is free for admitted Fellows - see the FAQ below for more information.

Fellows have the option to participate in the program either in person in New York, San Francisco Bay Area, Boston New, Washington DC, or online.

Leverage your degree as a data scientist

Training that links your analytical skills to job opportunities.

Free tuition for Fellows

Employer-paid Scholars keep the program free for admitted Fellows.

Mentorship from industry leaders

Learn from alumni and senior data scientists, and build your professional network.

Jumpstart your data scientist job search

Opportunities at top innovators in tech, healthcare, and finance with typical base pay ranging from $100K - $125K and as high as $150K.

Smart, passionate Fellows

Make the transition from academia with a selective peer group excited to learn and collaborate.

Build a series of miniprojects

Gain hands-on experience applying the tools employers value to real-world datasets. All powered by a 100-node cluster.

A few of our 250+ hiring and training partners:

Yelp
Flatiron Health
Foursquare
Mashable
Genetech
NY Times
Capital One
Pfizer
1010data
Microsoft
Ebay
JP Morgan

Testimonials

David Wallace

"TDI provided the opportunity to work with an incredibly intelligent and motivated group of people on difficult problems that were directly relevant to Data Science. [The] collaborative atmosphere, coupled with a very strong curriculum and knowledgeable mentors, really helped me to take my programming and machine learning capabilities to the next level."

David Wallace, Amazon

Johns Hopkins University

Brian Farris

"The most valuable thing I got out of The Data Incubator was the ability to meet people from industry through the partner panels and happy hours. [It] was an extremely efficient way to do a lot of networking in a short amount of time, which greatly increases the chance of finding a job. It is much easier to initiate a dialogue with a hiring partner if you have already met someone from the company in person."

Brian Farris, Capital One

Columbia University

Xia Hong

"Completing miniprojects on diverse and up-to-date topics really helped me to be confident about how to apply my technical skills to solve problems in practical situations. The hands-on experience from end to end, especially the relevance of the techniques to that in industry, is going to be a long-term benefit for me and certainly for any previous and current Fellow."

Xia Hong, LinkedIn

Emory University

With loads of data you will find relationships that aren’t real.
Big data isn’t about bits,
it’s about talent.
Forbes Magazine

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The next program (both in-person and online) will be 2019-04-01 – 2019-05-24. Sign up here for the latest information (including updates and deadlines) or to start your application.

Sign up here for the latest information (including updates and deadlines) about future sessions.

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Frequently Asked Questions

Ninety percent of all the world's data was generated in the last two years. Every 2 days, we generate as much data as all of humanity did up to 2003. Data scientists have the analytical and programming skills needed to extract valuable knowledge out of the data. The unique combination of skills that data scientists have is used across many industries for projects such as:

  • Parsing unstructured electronic medical records to detect new risk factors for cancer
  • Poring through educational app data to glean insights on how students learn
  • Forming personalized recommendations for restaurants and bars for millions of users
  • Predicting crime based on social network data
  • Crawling through stock market data for hidden price signals

The demand for data scientists is growing exponentially [1, 2] and IBM estimates that by 2020, the number of jobs for US data professionals will increase by 364,000 openings to 2,720,000 [3]. New York City, home to more Fortune 500 companies than anywhere else in the world, is quickly becoming a center for data science. Washington DC, with a high concentration of both corporate and government employers, has emerged as a hotspot for data science, with large corporations drawn to its highly skilled talent pool. Growth in Silicon Valley has also driven the data science market in the San Francisco bay area, with more and more companies relying on data science talent to scale their businesses. The competition for talent has led to compensation packages for talented first-year data scientists in the range from $100K to $150K.

[1] "Big Data Needs Data Scientists or Quants" (Forbes Magazine, 2012)

[2] "What Are The Odds That Stats Would Be This Popular?" (New York Times, 2012)

[3] "The Quant Crunch: How the Demand for Data Science Skills is Disrupting the Job Market" (IBM, 2017)

We consider any of the following applicants:

  • Anyone who already has a master's degree or PhD. You do not need to currently be a student in order to apply as long as you already have a master's or PhD. Faculty and postdocs are also welcome.
  • Anyone who is in the process of earning a master's degree or PhD. We recommend master's students be in their last semester of coursework at the time they attend the program and PhD students be within six months of defending their dissertation.

The program is geared towards helping participants find a job in the private sector and we are looking for candidates who want to start within 1-2 months of completing the Fellowship. If you are interested, we encourage you to apply.

We accept international students for the program and encourage them to apply.

However, we are not lawyers and cannot provide legal advice. To the best of our understanding, you may participate in the program if you have a visa that grants work-authorization, e.g. H-1B, TN, L-1B visas or F-1 students on Optional Practical Training (OPT), so long as the program is incidental to your status, or if you have any visa that allows you to be in the country to attend meetings, e.g. a visa status which allows for participation in professional seminars and/or non-academic, short course of study such as the B-1 visitor visa or the Visa Waiver Program. Please consult an immigration attorney for additional guidance. If you need an immigration attorney, consider using Adam Moses at Wildes Weinberg.

There are three main components to the program:

  • Weekly Projects. You'll build a series of mini projects to showcase your programming and mathematical talents. These projects will help you build your data science skill set using real world data to solve business problems.

  • Capstone Project. Using a data set of your choice you will build a working web application to showcase your talents for employers.

  • Interviews with employers. TDI works with over 300 employers in a variety of industries. Those employers play an active role in our programming throughout the cohort, attending events with students, and hosting panels on their industries.

Our program aims to build on the preparation you received in your academic training, by developing key skills such as:

  • Software engineering and numerical computation. Numerical techniques for optimization and vectorized linear algebra. Programming tools including Python, numpy, scipy, scikit-learn, matplotlib.

  • Natural language processing. Handling unstructured data, stemming, bag of words, TF/IDF, topic modeling.

  • Statistics. Hypothesis testing, regression and classification, ensemble methods, cross-validation, variance-bias decomposition, data normalization.

  • Data visualization. Including geographical and temporal data. Packages like d3, ggplot, matplotlib.

  • Databases and parallelization. SQL, Hadoop, MapReduce, Spark, TensorFlow.

In addition to our technical curriculum, staff supports students in all aspects of the job search.

  • Resume building. We assist in building a resume that translates your academic experience for industry employers.

  • Interview Prep. Over the course of the program we cover every aspect of the data science interview process, from technical coding interviews to behavioral and onsite interviewing.

  • Placement Assistance. Throughout the program our team works with you to identify the kinds of employers that would be the best fit for you, and to facilitate your application to those employers.

  • Job placement assistance. Our staff works closely with Fellows to identify their unique interests and skills to facilitate placements with our industry partners.

  • Tuition free. The program is free for admitted Fellows.

  • Hands on experience. All of our projects are designed to give you experience with real data sets, solving real problems.

  • Onsite instructors. Every location has an onsite Data Scientist in Residence to lead discussion and assist students.

  • Mentorship from industry leaders. Learn from alumni and senior data scientists, and build your professional network.

  • Cohort style program. Make the transition from academia with a selective peer group excited to learn and collaborate. We aim to keep each cohort small, fewer than 20 students per location, to maximize your interaction with our Data Scientists in Residence.

The program is in partnership with the Fellows and while we provide our Fellows with a lot, a few things are expected in return:

  • Make a commitment to participate full time. Fellows are required to participate in the program in person. This means moving to New York, the San Francisco Bay Area, Boston, or Washington DC, for the duration of the program. We expect Fellows to be in attendance for a standard 9 am - 5 pm work day, including occasional evening events. Scholars have the option to participate online, but we still recommend making a full-time commitment to the program for eight weeks.

  • Make a commitment to work as a data scientist in industry shortly after completing the program. We ask that you interview with our hiring companies during and immediately after the program. Ideally Fellowship candidates will be ready to start work within 1-2 months of completing the program.

  • Decline to work with external recruiters while in the program. In order to keep the program free for Fellows we do require that Fellows job search exclusively with our hiring partners during the program.

We welcome applications from anyone who has already obtained, or in the process of completing, their master's or PhD. If you are interested, we encourage you to apply. We recommend master's students be in their last semester of coursework at the time they attend the program and PhD students be within six months of defending their dissertation.

Absolutely! Candidates with industry experience are welcome to apply, as long as they have a completed Master's or PhD.

We require all applicants to be familiar with at least one programming language. While the program emphasizes Python, many of our applicants have experience with other languages, and varying degrees of coding experience. If you have no programming experience, we recommend starting with our Data Science Foundations Course which is designed to help students prepare for the Fellowship.

Applicants usually have a strong background in probability, statistics, and experience with programming, scripting, or statistical packages. We don't, however, have any strong preferences about academic discipline. We've had successful Fellows from backgrounds as diverse as Anthropology, Political Science, and Sociology, as well as Mathematics, Physics, Chemistry, and many others. If you are interested, we encourage you to apply.

Interested in the Fellowship but want to brush up your skills before applying? Read through this blog post to learn about some of the most important foundational skills for data science and to access resources to help you develop them.

Our alumni have gone on to take prestigious jobs in data science all over the country. Here's what they have to say about the program:

  • Dorian Goldman (hired by the NYTimes): "The Data Incubator team did an incredible job of emphasizing the most important and fundamental concepts that a data scientist needs to know in his career - I know, because all of these things were confirmed in my first week at my new job."
  • Justin Bush (hired by Palantir): "Already by the second and third week of the Data Incubator there were companies contacting me that may not have noticed my resume so readily otherwise. I also got a tremendous exposure to the variety of data science jobs out there, something that would not have happened had I taken a job directly out of grad school."
  • Brian Farris (hired by Capital One): "It was an extremely efficient way to do a lot of networking in a short amount of time, which greatly increases the chance of finding a job. It is much easier to initiate a dialogue with a hiring partner if you have already met someone from the company in person."
  • Sam Swift (hired by Betterment): "The intense incubator experience was also a great way to quickly transition my thinking and language from academic abstraction to business pragmatism. Like miscommunication between any two fields, I found that there was lots of common ground on ideas, but that it was obfuscated by specialized jargon on both sides."

For more on our alumni, check out our blog.

The tuition fee is paid for by hiring employers. The only cost for all Fellows is the cost of hosting a server in the cloud, which is required for running the course material. In-person Fellows are responsible for their own room and board during the Fellowship. We can assist Fellows in finding housing.

We accept only a very small number of applicants as Fellows, but will make additional offers to highly qualified candidates to participate as Scholars. There is a fee associated with Scholar participation, 50% of which is refunded to candidates placed with TDI hiring partners. If you would like to be considered for Scholar admission, the application process is the same and you should indicate interest on the application.

We also encourage anyone who is genuinely interested in data science as a career to reapply. Many of our most successful Fellows were not accepted on their first try, and used the time between application cycles to improve their application or technical skills.

Exponential Incentive Pie

Get rewarded for referring a friend. Or a friend of a friend …

Condition

Reward

Refer a successful fellow

$1024

Refer someone who refers a successful fellow

$512

Refer someone who refers someone who refers a successful fellow

$256

Refer ( someone who refers )10 a successful fellow

$1

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