The Data Incubator

The Data Incubator

A 6 week bootcamp fellowship in NYC preparing PhDs
for careers as data scientists and quants.

Be a Data Scientist    Hire a Data Scientist

The Data Incubator

Use your PhD to solve real-world problems.

The Data Incubator is an intensive six-week bootcamp that prepares the best science and engineering PhDs to work as data scientists and quants. It identifies fellows who already have the 90% difficult-to-learn skills and equips them with the last 10%: the tools and technology stack that make them self-sufficient, productive contributors. The program is free for fellows. Employers only pay a tuition fee if they successfully hire.

Leverage your PhD

Training that links your analytical skills to job opportunities

Employer paid scholarships

Tuition is free for admitted fellows

Mentorship from hiring firms

Learn from senior data scientists at our hiring companies and build your professional network

Jumpstart your career

Opportunities with the most innovative employers in technology, healthcare, and finance with \$100K - \$200K starting compensation

Smart passionate PhD Fellows

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

Build a portfolio project

Showcase your knowledge by applying the tools that employers value to proprietary industry data

A few of our great employers

Etsy
Flatiron Health
Foursquare
Mashable
Morgan Stanley
NY Times
Capital One
Ebay
Data Scientist: The Sexiest Job
of the 21st Century
HARVARD BUSINESS REVIEW

People

Dr. Michael Li, Executive Director

Michael has worked as a data scientist (Foursquare), quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He did his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar.

At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup that let him focus on what he really loves.

Dozens of amazing mentor data scientists including ...

Robert Almgren

Cofounder and Head of Research, Quantitative Brokers

Joanne Chen

Senior Data Scientist, Truveris Health

Nellwyn Thomas

Director, Data Analyst Team at Etsy

Exponential Incentive Pie

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140,000 – 190,000 more deep analytical
talent positions needed.
McKinsey Global Institute

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

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 the data. The unique combination of skills that data scientists have are 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
  • Form personalized recommendation 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 McKinsey estimates a need for 140,000-190,000 more data scientists over the next few years [3]. New York City, with a burgeoning technology sector and home to more Fortune 500 companies than anywhere else in the world, is quickly becoming the center for data science. The competition for talent has led to compensation packages for talented first-year data scientists in the range from \$100K to \$200K.

[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] "Big data: The next frontier for innovation, competition, and productivity" (McKinsey Global Institute, 2011)

There are four main components to the program:

  • Bootcamp modules. Short modules covering both the technical and non-technical skills necessary to succeed in industry. These are not mandatory so just attend the ones you want.

  • Seminars with mentor data scientists. Unlike academic research seminars, we promise these will actually make sense. Hear from the top data scientists in the world about what data science is like for them.

  • Build a portfolio project to showcase your programming and mathematical talents. Employers are naturally skeptical and it's way better to show than to tell. We'll guide you through choosing and building a project using the skills and techniques that they care about.

  • Interview with amazing employers. Meet employers looking for top applicants.

The program builds on your scientific training and provides you the skills needed to quickly have large industry impact. While a PhD or postdoc is excellent preparation, our experience has shown that academic researchers often lack a few key skills. The curriculum includes:

  • Software engineering and numerical computation. Numerical techniques for optimization and vectorized linear algebra. Programming tools including python, numpy, scipy, scikit-learn, matplotlib. Data visualization including d3, ggplot.

  • 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.

  • Databases and parallelization. SQL, Hadoop, MapReduce, Hive.

Succeeding in industry is as much about soft-skills as technical ones. We cover some of the basics:

  • Communication skills. Academics and people in industry communicate in very different ways. We'll work with you to avoid common pitfalls and distill your research and data science insights into messages that will be appreciated by non-experts.

  • Networking. Meeting people is really important for your career but there are half a dozen subtle mistakes that young professionals frequently make. We'll help you avoid them.

  • Practice interviews. Technical interviews can be notoriously tough. We help our fellows prepare so that they know what to expect.

  • Leverage your PhD.  Training that links your analytical skills to job opportunities.

  • Employer paid scholarships.  Tuition is free for admitted fellows.

  • Mentorship from hiring firms.  Learn from senior data scientists at our hiring companies and build your professional network.

  • Jumpstart your career.  Opportunities with the most innovative employers in technology, healthcare, and finance with \$100K - \$200K starting compensation.

  • Smart passionate PhD Fellows.  Make the transition from academia with a selective peer group excited to learn and collaborate.

  • Build a portfolio project.  Showcase your knowledge by applying the tools that employers value to proprietary industry data.

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 be a part of the program. This means moving to New York City for the duration of the six week program and being there every day during the workweek, interacting with the other fellows, and working on your portfolio project. You should really think of this as a mini-internship.
  • 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 immediately after the program. If there's another company that you would like to interview with, just notify us in advance so that we have a chance to work with them as a hiring company. Most employers would prefer you start within two to three months of an offer.
  • Decline to work with external recruiters while in the program. We provide training to fellows for free and compete with external recruiters who charge for just making a placement without providing any training. Working with them prevents us from investing in curriculum and improving the program for future fellows.

We welcome applications from anyone who has or is about to receive their PhD from any STEM field, including math, physics, chemistry, biology, psychology, social science, operations research, neuroscience, and many others. This includes postdocs, faculty, PhD candidates about to graduate, and people with PhDs in industry. The program is geared towards helping them make a transition to the private sector from academia and we are looking for candidates who want to start within two to three months of completing the bootcamp.

Please request an application here to get on our email list. While we are only taking applications from PhDs at this time, we are looking to expand the criteria shortly.

We encourage foreign students graduating from US institutions to apply. While you can participate in the program, you will need to apply for an F1-OPT visa extension.

We are looking for people with strong scientific training who feel comfortable working with research data and have some experience with programming, scripting, or statistical packages.

The program is completely free and the tuition fee is paid for by hiring employers. The only cost for fellows is their room and board during the fellowship and we can assist fellows in finding housing in New York City.

Contact us

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