The Data Incubator

Boot camp from Categories New York

The Data Incubator is a 6 week fellowship training and placing PhDs as data scientists and quants in NYC and the Northeast. It identifies the best science and engineering PhDs who already have the 90% difficult-to-learn skills necessary for being a data scientist or quant and equips them with the last 10% of enabling training in the right tools and technology stack to leverage their expertise and make them productive on day one.

The program is free for fellows and hiring companies only pay a tuition fee if they successfully hire a fellow from the program.

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.

Who can apply:

The Data Incubator welcomes 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.

Hiring Partners

Etsy, FlatIron, FourSquare, Mashable

The inaugural program will be from June 9 – July 18.

Data Incubator


TypeIn class
FocusBig Data
Started in2014


Length6 weeks
Class sizeN/A
Sessions per yearN/A
Dedication per weekFull time
Minimum skill levelPhD, postdocs,
PhD candidates
Placement test
Coding challenge
Prep work before classes startN/A


Total Cost

Exclusive discount to visitorsN/A
Refund (if accepted job through program)No
Financing / ScholarshipNo


Student VisaNo


Phone #N/A
CityNew York, NY


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  • William Shi

    I was a fellow at The Data Incubator. It was an amazing program: I learned a lot about machine-learning, ETL, spark, and mapreduce and now have a great job!

    • MH

      Hi William,
      What was the number of participants?

  • Sue

    Do participants have to devote full time over the six week period to the program? What if i have a previously scheduled presentation at an international conference during the program period? Would i be able to take off a few days to attend the conference?

  • Nick Bauer

    Here’s a warning: They don’t seem interested in training people from scratch, despite what they claim. They appear only interested in training people who already have a pretty good knowledge base and could possibly already get a good job in the field, based on the application process. And their application process is amateurishly executed at best. The program itself might be just fine (it seems to be well regarded by those who do get in), but they seem like they’re probably just trying to get a financial piece of the pie for demand for these positions and working off desperation for recent PhDs trying to get a job in a marketplace that is extremely hostile to on-the-job training.