We’re excited to introduce you to Lili Tang, a volunteer Data Expert who worked on our Data Integrity project with Medic Mobile, one of our expert partners under our Frontline Health Systems Impact Practice. A Senior Data Scientist at Sonos, Lili has a background in both software engineering and data science. As a Data Expert, she is unfazed by messy data and enjoys tinkering and hacking to understand underlying trends and find answers to a project’s data science questions. She holds a B.S. in Mathematics and an M.S. in Computer Science.
To learn more about Lili’s journey with Medic Mobile in her own words, read on!
Tell us a little bit about yourself and your background.
I have my bachelor’s degree in Mathematics and master’s degree in Computer Science. In industry, I’ve been both a software engineer (working primarily in backend, devops, and data) and a data scientist. I’ve fallen in love with data science because it combines math, programming, and heavy interaction with stakeholders. In my spare time, I like to hike, run, and eat lots and lots of sushi!
Can you briefly describe the project that you’re currently working on?
I work as a Data Expert on the Medic Mobile data integrity team. Medic Mobile’s mission is to improve health in communities that are hardest to reach by using open source tooling to track and monitor patients. Our main deliverable for this project was a codebase for identifying key IoP (inconsistent or problematic) data issues. During the first half of the project, I spent time performing exploratory data analysis to find IoP data within the dataset provided by Medic Mobile. During the second half, I worked on our codebase to develop tests for detecting the IoP data our team found during the exploratory phase.
What surprised you most about the project?
During the exploratory phase, it felt somewhat overwhelming because each of the Data Experts were finding different kinds of IoP issues. It felt like a lot to wrap up in a single codebase and a lot of work to be able to write database tests for validating the data. The Data Ambassador for this project found the perfect tool, dbt, to be able to test all our IoP findings using built-in tests and writing custom SQL tests. It was awesome to discover this too. It ended up being easier than anticipated and worked great for our use case.
What is the highlight of the project so far?
Collaborating and learning from all the other members of the team. I think all of us had similar skill sets, but also had our own experiences as data scientists. I loved hearing everyone’s input on data findings. It taught me other ways of looking at data and how to find IoP. Being able to speak with other team members on a weekly basis gave me other ways to approach a problem. This was truly a great learning experience for me.
What data science skills have been most useful for this project?
The most useful data science skills has been my experience with Python and, in particular, with pandas (Python Data Analysis Library). This project required analyzing the data in a flexible way and pandas allowed me to do just that. I loved being able to use Python and some of the libraries I’m most familiar with while working on this project because it really helped me sharpen my skills using a new and exciting dataset.
How has this project shifted your perspective on doing data for good?
Before I joined DataKind, I never worked on a “data for good” project before, but had a lot of interest in working on one. After completing one, I can say that it really does take a team to see the completion of a successful high impact project. I would have never been able to do something like this on my own! It requires more than just Data Experts. It was super helpful having a Project Manager to track the progress, the Data Ambassador to coordinate meetings and organize presentations, and the DataKind team to give us the resources to be able to do the project like the virtual machines. It takes time and dedication from many people to be able to see a project to fruition.
If you could live anywhere in the world, where would it be?
Iceland. I fell in love with Gjian! It’s unlike any other place I’ve ever seen before. The whole country is beautiful.
If you could be any animal, which would you be?
Definitely a bird, it would be so cool to fly!
Our volunteers are the lifeblood of our mission. They’ve inspired people to use their skills in ways they never dreamed of. They’ve slayed misconceptions. They’ve shown organizations trying to make the world a more humane place how data science and AI can change the game. We’re honored (and thrilled) to feature their stories in DataKind’s Volunteer Spotlight series. Follow this series to learn about their impeccable skill sets, their work with our brilliant project partners, and what inspires them to give their time, resources, and energy to causes that matter.
