Data are becoming the new raw material of business
The Economist

Bringing Astronomy Down to Earth: Alumni Spotlight on Tim Weinzirl

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.  Tim was a Fellow in our Spring 2017 cohort who landed a job with one of our hiring partners, First Republic Bank

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

My education includes a B.S. in Physics from Drake University and a Ph.D. in Astronomy from the University of Texas at Austin. After grad school, I went overseas for a Research Fellowship at the University of Nottingham. Astronomers do a lot of coding relative to other fields, and having been coding in Python since 2006 for work, I was very familiar with the Python SciPy stack. Since 2014, I have also been volunteering time to data science and software engineering projects for a people analytics startup. This was extremely useful because it provided references in industry who could vouch for my data science skills.

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

I got several useful things out of The Data Incubator: Strategies for resume writing, experience building and deploying a live web application, and a comprehensive set of IPython notebooks that encapsulate the advanced features of scikit-learn, SQL, and big data tools (Hadoop, Spark).

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How to Catch ‘Em All: Alumni Spotlight on Yina Gu

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.  Yina was a Fellow in our Winter 2017 cohort who landed a job with one of our hiring partners, Opera Solutions

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

I received my PhD degree from The Ohio State University majoring computational chemistry. For my PhD research, I developed multiple predictive models and published web servers to solve various biophysics problems using machine learning and statistical methods in Python, R and Matlab. The data science skills and experiences I gained in my 5 years of PhD not only allow me to solve the fundamental scientific problems effectively and efficiently, but also enable my transition from academia to industry to solve the real-world challenges.

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

The 8-weeks intensive training at The Data Incubator really helped me to go deeper into data science field and get fully prepared for the essential skills to work in a big data industry with the cutting-edge analytics techniques, including programming, machine learning, data visualization as well as business mindset. Last but not least, I believe the networking with other very talented fellows are the most valuable thing I got out of TDI!

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Developing a Foundation for Data Science: Alumni Spotlight on Ryan Jadrich

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.  Ryan was a Fellow in our Fall 2016 cohort who landed a job at Austin based startup OK Roger

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

My PhD and postdoctoral work was in the field of statistical mechanics with a strong emphasis on the design of new colloidal materials. Such research has required me to develop a hybrid set of strong analytical math and computational skills—of which have been extremely useful for bridging into Data Science. From the deeper level understanding afforded by this mixed skill set, I feel well posed to leverage existing technologies as well as develop novel alternatives.  As an example of the latter, my forays into the fundamentals of Machine Learning helped me to develop a super-computing application capable of inferring the inter-particle forces an experimentalist must engineer to elicit a desired material property. This required the development of both an analytical framework and an underlying large scale molecular simulation element. Combining these general technical skills with what I learned at The Data Incubator, I feel well poised to be successful in a Data Science position

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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.

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Predicting Flight Delays with Random Forests: Alumni Spotlight on Stacy Karthas

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.  Stacy was a Fellow in our Winter 2017 cohort who landed a job with one of our hiring partners, AdTheorent

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

I received my Bachelor of Science degrees in mathematics and physics from the University of New Hampshire. I then went on to graduate school at Stony Brook University. I graduated with my master’s degree in Physics in December 2016. During my master’s degree, I did research in Nuclear Heavy Ion Physics with a focus on the analysis of gluons and their products as they traversed our detector. The data analysis, simulation, and clustering algorithms I worked on prepared me to become a data scientist because it was a physical application of many of the tools used by data scientists.

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

The Data Incubator gave me the chance to solidify my data science knowledge. It helped me pull together tools and concepts I had been using during all of my previous research experiences. I learned a lot of new machine learning concepts and how they could be applied to real world data.

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From Researcher to Algorithm Engineer: Alumni Spotlight on Anthony Finch

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.  Anthony was a Fellow in our Winter 2017 cohort who landed a job with one of our hiring partners, Afiniti

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

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I came into The Data Incubator with a Master’s degree in Computational Operations Research from The College of William and Mary. My Master’s program gave me a strong background in theory and in the practical application of machine learning, simulation, and optimization. I had a few internships as well, primarily in finance.

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

The Data Incubator gave me a lot of experience handling data in a way that I didn’t get in an academic environment. The data sets were big, messy, and realistic. In addition, I thought that the capstone was an excellent way to get into a more industrial environment. The Data Incubator required a lot of database management, web scraping, and the like, which I didn’t get in the academic setting I came from

I also felt that The Data Incubator gave me a number of excellent opportunities. It may seem frustrating at times, but the partners really do want to hire Fellows, and The Data Incubator’s salary and compensation ranges are very accurate (in my experience). I’m not sure I would have gotten the same response rate and offers if I hadn’t been applying through the fellowship.  

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Analyzing Time Series Data for Parkinson’s Wearables: Alumni Spotlight on Jordan Webster

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. Jordan was a Fellow in our Spring 2017 cohort who landed a job with one of our hiring partners, IronNet Cybersecurity

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

My background is in particle physics. As a physicist, I analyzed large datasets of particle collision images, and I used machine learning tools to classify rare and interesting collisions.

 

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

At The Data Incubator I I learned a whole new toolset for approaching data analytics. I was exposed to new concepts like language processing and map-reduce, which never arose in physics. Furthermore, I was coached on how to best market myself to employers.

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Ride-sharing for Senior Citizens: Alumni Spotlight on Aurora LePort

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. Aurora was a Fellow in our Spring 2016 cohort who landed a job with Verizon Wireless

 

Tell us about your background. How did it set you up to be a great data scientist?Version 2

I obtained my Ph.D. in Neurobiology and Behavior from UC, Irvine in 2014. I collected data related to brain activity representing autobiographical memory using Magnetic Resonance Imaging (MRI) for my dissertation. The accurate analysis of MRI data demanded the ability to preprocess, and clean data as well as automate the processing steps using Matlab and R. Understanding how to properly use these tools was instrumental towards acquiring a new programming language (i.e. Python). Furthermore, the ability to apply statistical concepts to analyze various forms of data from diverse scenarios was highly conducive towards becoming a well-rounded data scientist who excels at analyzing novel datasets.

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Solving Interdisciplinary Problems with Data Science: Alumni Spotlight on Wendy Ni

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. Wendy was a Fellow in our Winter 2017 cohort who landed a job with one of our hiring partners, Facebook.

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

I have a PhD in Electrical Engineering from Stanford University, where I’m currently a postdoc.  My doctoral and postdoctoral research focus on the translation of novel magnetic resonance imaging (MRI) technologies to clinical neuroimaging applications, and the extraction of “hidden” imaging biomarkers from conventional clinical images.  In my research, I utilized my engineering, programming, study design, and communication skills to solve interdisciplinary problems with real-world impact.  I am now pivoting to data science, because I want to use my quantitative and analytical skills to discover hidden insights and guide decision-making for immediate applications in industry.

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Making the Switch from Management Consulting: Alumni Spotlight on Armand Quenum

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. Armand was a Fellow in our Fall 2016 cohort who landed a job with KPMG.

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

I received my Bachelor’s degree in Mechanical Engineering from NC State University. After college, I became a management consultant specializing in program and strategic management. As a consultant, I saw the value of data-driven decisions and extracting insights from data. As a result, I decided to go back to school to obtain my Master’s in Systems Engineering. There I was introduce to R Programming software, data mining techniques, and applications of optimization. My Masters not only exposed me to data science, but it also provided me a framework to approach complex problems.

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