Call for applications for Data Science Fellowship 2019 in the USA. The Data Incubator is a Cornell-funded data science training organization. We run a free advanced 8-week fellowship (think data science boot camp) for PhDs looking to enter the 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.
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
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.
Data Science Fellowship 2019 Details:
- The United States of America
- The Data Incubator
- Fellows have the option to participate in the program either in person in New York, San Francisco Bay Area, Boston, Washington DC, or online.
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- 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 the 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.
Note: 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.
What will the Program be like?
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.
What kind of technical skills will I learn?
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, a 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.
Responsibilities of Fellows:
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 in 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 workday, 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 the 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
- Anyone who already has a master’s degree or Ph.D. You do not need to currently be a student in order to apply as long as you already have a master’s or Ph.D. Faculty and postdocs are also welcome.
- Anyone who is in the process of earning a master’s degree or Ph.D. We recommend master’s students be in their last semester of coursework at the time they attend the program and Ph.D. students be within six months of defending their dissertation.
See the FAQ for more information.
How to Apply for Data Science Fellowship 2019?
- Deadline is not mentioned on their official website. Apply as soon as possible.