Online United States of America
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.
Fellows have the option to participate in the program either in person in New York, San Francisco Bay Area, Boston, Washington DC, or online.
- Leverage your degree as a data scientist: Training that links your analytical skills to job opportunities.
- Mentorship from industry leaders: Learn from alumni and senior data scientists, and build your professional network.
- Smart, passionate Fellows: Make the transition from academia with a selective peer group excited to learn and collaborate.
- Free tuition for Fellows: Employer-paid Scholars keep the program free for admitted Fellows.
- 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.
- 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.
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.
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.
The next program (both in-person and online) will be 2019-09-16 – 2019-11-08. Sign up here for the latest information (including updates and deadlines) or to start your application.
Opportunity is About:
Candidates should be from:
Description of Ideal Candidate:
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.
Deadline: August 03, 2020
Cost/funding for participants:
What are the benefits for Fellows?
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.