This past summer, I was selected as a fellow for Harvard Data Science Initiative’s Public Service Data Science Fellowship to work at a nonprofit organization. I worked at Austin Pets Alive!, a nationwide-leading no-kill animal shelter. APA! is a unique animal shelter in that it only brings in difficult-to-place animals who otherwise would have been euthanized from other shelters. In order to make sure these animals find their forever family, APA! actively initiates various types of innovative programs. For example, APA! has a technology team, which is a group of APA!’s tech employees and volunteers dedicated to optimizing and improving no-kill shelter operations through programming and data science skills.
During 10 weeks of my summer internship, I worked in various data science and software engineering projects. My main project was building a Matchmaking App, a web application that works like Tinder to match potential adopters with dogs. When APA! visitors interested in adopting dogs sign in at the reception area, the web app uses their home environment information to recommend dogs that they can take home, prioritizing the long-stay dogs in need of home. I built the web app’s frontend with HTML5/CSS/JavaScript/jQuery, built its backend using python’s Flask framework and mySQL database, and deployed the app using Docker. The Matchmaking App is currently being used by APA! visitors who are interested in adopting dogs. The app not only matches visitors with the animals they can adopt, but also streamlines the adoption process by facilitating the work of the matchmakers (adoption managers), and therefore helps shelter dogs get adopted.
For my second project, I assessed the dog adoption capacity of Travis County, where APA! and Austin is located in. Because APA! brings in animals even from outside of county, we wanted to assess whether APA!’s out-of-county intakes are oversaturating Travis County’s adoption capacity, thereby negatively impacting Travis County city shelter’s (Austin Animal Center) adoption rates. I collected and cleaned AAC and APA!’s dog intakes and outcomes data (AAC’s data were publicly available here) and performed statistical and mathematical analyses to determine whether such was the case. We are still reviewing the results of the report for final publication, and I will write a separate blog post about the details of the report soon.
My other fun miscellaneous projects were: building a slack chatbot called ‘apabot’ that helps APA! foster team to easily retrieve an animal’s vaccination history or future medical appointment information.
I also created a heatmap generator website that builds a heatmap of Travis County when an APA! employee inputs a csv file of count data by zipcode. Such data visualization can easily capture donation/adoption/fostering trends in the Austin community and help APA! team make better decisions such as for targeted marketing campaigns.
Overall, my public service summer internship was a valuable experience that helped me become a full-stack data scientist. First, I got to build everything from scratch until it was deployed at a production level. It was very rewarding to solve real-world problems and actually see my tangible working products getting used by shelter employees and visitors. Moreover, I learned a lot by getting advice from APA! tech employees and volunteers in various tech fields, such as data management, statistics, and user experience. Last but not least, I really enjoyed volunteering as a dog walker and photographer at APA! and meeting all the lovely shelter dogs!
Patches 
Love Bug 
Chickpea 
Boo 
Janet Jackson 
Chowder
Even after the internship at Austin, I am still working as a remote tech volunteer for APA!, currently maintaining and upgrading some new features for the matchmaker app based on user feedback. I hope to get involved soon in other interesting data science and software engineering projects to ultimately help shelter animals find their homes, so both people and animals can have happier lives.
Rachel Moon 