Data are becoming the new raw material of business
The Economist


Predicting Visa Wait Times: Alumni Spotlight on Sudhir Raskutti

At The Data Incubator we run a free eight-week data science fellowship to help our Fellows land industry jobs. We love Fellows with diverse academic backgrounds that go beyond what companies traditionally think of when hiring data scientists.  Sudhir was a Fellow in our Fall 2016 cohort who landed a job with one of our hiring partners, Red Owl

Tell us about your background. How did it set you up to be a great data scientist 

I am a PhD in computational astrophysics from Princeton University with a background in electrical engineering. Astrophysics gave me both a reasonably strong problem solving background as well as the ability to deal with quite terrible data.

What do you think you got out of The Data Incubator?

The Data Incubator was really useful in a few ways. Firstly, I got a broad brush overview of the tools and technologies most commonly used in Industry. Obviously in 8 weeks, you’re not going to learn all of the tools and concepts in depth, but the Incubator was good at giving a frame of reference for asking deeper questions. More importantly, it was really good at setting up a network and providing a framework for reaching out to employers. It’s a huge advantage to meet employers face to face before reaching out to them, and to have something to show to them and talk about.

What advice would you give to someone who is applying for The Data Incubator, particularly someone with your background?

It’s a really good way of getting a concrete idea of what’s expected from you in a Data Science interview or job. It’s also very good at teaching you how to sell yourself and how to reach out to employers. A lot of the maths and machine learning won’t be new to someone with a quantitative PhD, or an engineering background, but the specific tools that are used will be and it’s worth it for that. It’s definitely worth spending a bit of time beforehand both building on your project idea, and covering topics in machine learning, because it gives you a lot more time during the Incubator to focus on connecting with employers.

What’s your favorite thing you learned while at The Data Incubator? This can be a technology, concept, or whatever you want!

I really liked Flask and the relatively clean interface for building a web application. I’d already done some machine learning before coming here, but the ability to translate a cool project into a web application was really great.

Could you tell us about your Data Incubator project?

My project for the Data Incubator was on predicting the success rate, and wait times of applications for a US Green Card or Visa. I’m a student here on an F-1 Visa and I find it both frustrating and a little terrifying dealing with US Immigration. With that in mind, I wanted to make things a little more transparent for immigrants to the US, and try to understand what factors are important in making Green Card and Visa applications successful. To do that, I used data from US Immigration Services to predict the success of an application on the basis of a number of features such as the applicant’s country of origin, their expected wage, their education level, and what field they work in. My hope is that both employers and immigrants will be able to use my application and get a feel for how successful they are likely to be and more importantly what they can do to help themselves out, before they commit a year of their life and lots of money to the application process.

You can learn a bit more about Sudhir’s project here: http://getmein.herokuapp.com/index

 

Tweet about this on TwitterShare on FacebookShare on LinkedIn

Back to index