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PyDev of the Week: Aileen Nielsen

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PyDev of the Week: Aileen Nielsen

This week's PyDev of the Week is Aileen Nielsen, a data scientist who recently gave a talk at PyCon 2017 and is an active Python user in the data science community.

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This week, we welcome Aileen Nielsen as our PyDev of the Week. Aileen has been using Python in the data science field for a while now. She recently gave a tutorial on Time Series Analysis at PyCon 2017 and she also did a talk on NoSQL Python at PyData Amsterdam 2016. Let’s take a few moments to learn more about our fellow developer!

Can you tell us a little about yourself (hobbies, education, etc.)?

I’m a software engineer at One Drop, a diabetes management platform. We’re trying to help people better understand and manage their chronic conditions with the use of technology, data analysis, and expert coaching.

I spent a lot of time in school (law school, ABD in physics grad school), so I consider myself an eclectic person as far as academic interests, and I like to read non-fiction in lots of areas. Right now, I’m most interested in non-fiction books about spying and organized crime. My hobbies are traveling and hiking. When I’m not working, I try not to be in front of a screen.

Why did you start using Python?

I "grew up" with R and some proprietary data analysis software packages I used in physics grad school (Igor, Matlab). However, I was frustrated with proprietary software solutions because they’re not portable and not so well-discussed on forums like Stack Overflow.

Over time, I got more drawn into Python because the documentation is user-friendly and well-presented. Also, the Python community is so active and welcoming both online and in person that it’s easy to get started. I like that Python has such an eclectic base of industry, academic, and hobbyist users.

What other programming languages do you know and which is your favorite?

I have done most other work in R, C++, and Objective-C. Apart from Python, my favorite programming language is C++ because the syntax is so precise but also so wonderfully complicated.

What projects are you working on now?

I like to give talks about Python and how it relates to my work. At the moment, I’m putting together a four-part tutorial on Machine Learning for Healthcare in Python and R.

Which Python libraries are your favorite (core or third-party)?

The obligatory answer in my line of work is pandas, numpy, and scipy. That said, I’ve spent a lot of quality personal time with scrapy.

Otherwise, I tend to go looking for really specific algorithms not covered in scipy and related packages. In that case, I often find GitHub is my best friend and that most algorithms I look for have several well-implemented gists I can use to see examples of what I want to do.

Is there anything else you’d like to say?

I’ve gravitated towards the Python community because it is so open, welcoming, and active. Apart from its beautiful syntax, Python offers lots of opportunities to get to know interesting people working on fantastically interesting problems. I believe Python will keep growing so long as this continues to be the case.

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Topics:
python ,data science ,big data

Published at DZone with permission of Mike Driscoll, DZone MVB. See the original article here.

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