2020 has been an unprecedented year and Alteryx’s internship and co-op program is no exception. In the midst of a global pandemic, we quickly pivoted to a virtual program to keep our team safe and healthy.

In total, we hosted 5 Software Engineering Interns and Co-ops this summer and fall in the Alteryx Innovation Labs where we build products to democratize machine learning.

Our goal is to give interns exposure to high-impact projects, as well as events and activities that enabled learning, growth, and social connections including:

  • Hearing from company executives via our virtual Intern Unplugged speaker series
  • Assembling STEM kits for youth in Boston as part of virtual volunteering through the Alteryx for Good program
  • Presenting their projects at team-wide All-Hands and lunch & learn events called Feed Your Mind
  • Virtual social activities like intern lunches, game nights and quarantine happy hours

Our interns and co-ops had a few things to say about the exciting projects and work they did at Innovation Labs.

Ethan Tu, Predictive Feature Selection

I worked on a research project for Featuretools to do feature selection prior to calculation by learning from past datasets. The cool thing about this project is that it addressed a problem no one else solved for previously: predict which features from automated feature engineering provide value to prediction problems without having to calculate the feature values.

I was able to create an end-to-end solution and produce machine learning models that predicted feature importance using only dataset metadata that ended up being better than random selection. To train and tune these models, I used a Python library built by Alteryx called EvalML.

Outside of my project, the internship allowed me to improve my presentation skills thanks to 1:1 coaching from my manager and VP and also gave me a chance to contribute to four Featuretools releases.

Becca McBrayer, Natural Language Processing for AutoML

I had the chance to focus on multiple projects while at Alteryx. The first was adding support for text data in EvalML, which was released in October along with a tutorial I authored to go with it.

Beyond that, I reworked EvalML to support machine learning pipelines as more complex graphs of components, rather than just linear computation. Also, I added dimensionality reduction to AutoML search, to help the process run faster.

With this virtual co-op, I learned how to make connections and advocate for myself in a professional setting. Additionally, I’ve developed good habits for writing good code while collaborating with a team and providing useful feedback during the code review process.

Chris Bunn, Parallel Computation for Automated Machine Learning

This year, I returned for my second internship to work on an open source AutoML library called EvalML. I was excited for this because during my first internship I worked on the first version of performance testing and benchmarking framework for EvalML.

This time around I worked more on the library itself by designing and implementing a new API that allows fitting pipelines in parallel. This will help to reduce the amount of time it takes for our users to complete an AutoML search.

This work required me to learn and use Dask, a parallel computing library for Python, extensively. Additionally, I contributed to general bug fixes and improvements to EvalML.

Clara Duffy, Python Libraries for Data Scientists and Developers

This year, I returned for my second internship and had the opportunity to choose which products and projects are of the most interest to me and will allow me to make the largest impact at Alteryx.

In the beginning, I focused on EvalML and integrated new machine learning pipelines into the library. From there, using my knowledge about Python library development, I created a complementary Python client library and SDK for a new code-free machine learning product being built at Alteryx. I enjoyed learning about the process of creating a larger scale enterprise product while seeing the impact that my contributions have had on the team.

Note: Learn more about Clara’s internship experience by tuning in to the Alter Everything Podcast, Episode 72.

Reza Akhtar, Code-free Machine Learning

I worked on the user interface and backend APIs for the Innovation Labs’ newest product.

This product helps business analysts, data scientists, and less experienced data workers leverage machine learning without the need to write code. I’ve contributed to various features that provide users visuals to better understand their data and the predictive models they are building.

It has been fun to work on a project that gave me my first major frontend engineering experience, so I learned new technologies like TypeScript, React, and Redux.

Are you interested in exploring early in career opportunities with Alteryx’s Innovation Labs? Apply for 2021 Software Engineering Summer Internship and Recent Grad opportunities or visit www.alteryx.com/careers.