Fellowship to Maximize Practical Experience

Fellowship Application Process

Step 1: We offer open enrollment.  Fist complete this form

Step 2: Work on a challenge problem and submit your results

Step 3: Schedule a time to speak with a mentor or ex-fellow

Program Location
Name *
Name
http://
When can you start? *
When can you start?
We have a rolling admission policy. Since there is no set curriculum, we admit fellows based on the needs of our projects.
Background
Background
Familiar with ML theory & math
Know how to code
Proficient in stats
Understand distributed systems

Fellowship Frequently Asked Questions

 

How long and where is the program?

The program is 4 months long and based in the San Francisco Bay Area.

Can the fellowship program be done remotely? Also do you sponsor visas?

No, you need to be present in person as we believe one learns data science my interacting and exchanging ideas in person. Moreover we mentor the fellows and therefore for effective mentoring the fellows need to be present in the office. No we don't have the capabilities to apply for visas for fellows. 

How much does it cost?

The program is free to the fellows.

Bay Area is expensive, do you offer any stipend or living accommodations?

At this point we don't offer any assistance.

How is this program different from other Data Science programs?

The fellows work on actual industry sponsored projects. These projects span multiple months and the fellows have an opportunity to interact directly with the sponsors. The goal is to deliver a product and not a project. There is also daily interaction with mentors and on Fridays we get industry visitors who share their Data Science experience with the fellows. 

What happens to fellows after they graduate? What jobs do they get?

Our fellows are now in data science roles at Uber Advanced Technologies Center, Enlitic, Sentient Technologies, Yelp, Orange, etc.

What type of projects will I get a chance to work on?

We work on quantitative finance and startup projects.  Our work with hedge funds, prop traders and asset managers represents the majority of focus.  This work is very demanding and requires us to do cutting edge research.  We spend approximately 20% of our time working on startups in a variety of industries to help the community and give fellows a more diverse set of experiences.

What does the day-to-day look like?

Majority of the time is spent pair programming.  We pair up a fellow more proficient in quantitative skills with a fellow more proficient in software development. The project team typically consists of 2 fellows working under supervision of a mentor.  

We have daily scrums, and we are very diligent about it. We have internal slack channels, shared github repos and trello boards. We have a weekly retrospective and iteration planning. 

What tools will I get a chance to learn?

We are primarily a python shop but fellows are free to use whatever tool and technique they believe is best suited to the problem. We typically use a variety of machine learning libraries including TensorFlow, Keras, XGBoost, etc.

What percentage of the fellowship is actual model building?

Model building is an iterative process. Typically, we spend 50% on data munging, 40% on modeling and the remaining on making the project user friendly and ensuring that the model is usable.