How to ace the MLDS interview at Cash App

With Christa Santa-Donato, MLDS Recruiter

We know interviewing can be nerve-wracking, but it doesn’t have to be. It should spark great conversation and be an opportunity for you to interview our team, too.

You’re probably wondering what it’s like to interview for a Machine Learning and Data Science (MLDS) role at Cash App. To take some of the mystery out of interviewing, we sat down with Christa Santa-Donato, a Recruiter on the team, to walk you through the process and share some tips on how to ace it.

Meet your guide

“Everyone I met with was excited, and it was clear they enjoy working here,” says Christa Santa-Donato, a Technical Recruiter at Cash App, about her interview experience before joining the company. “You don’t always get that from interviews, so it left a mark on me.”

Christa previously owned a business knitting headbands, and she used Square for payments, so she was always drawn to the Block ecosystem. “I joined Cash App from Square because the mission of the company resonated with me—and I wanted to apply my tech experience to a growing startup,” she says.

After working as a tech recruiter for nine years, Christa now partners with hiring managers on the Machine Learning and Data Science (MLDS) team to address their hiring needs and fill open roles. 

With a lot of innovation happening in the ML space right now, Christa loves collaborating with that part of the Cash App organization: “Everyone is really passionate about their work and the recruiting process—they really care about candidates,” she says.

About the MLDS team

The MLDS team is responsible for many important parts of Cash App’s product. It spans several areas, including:

• The Machine Learning (ML) team, which includes the modeling team—which builds models—and the infrastructure team, which builds the infrastructure for those models

• The Product Data Science team, which is embedded into the various product streams at Cash App

• The Business Intelligence team, which works as part of the Product organization

The operating principles the team embodies really well are climbing walls and competing on creativity. The team continues to move fast and release products in the face of rapid change, a quickly growing team, and a constantly evolving MLDS landscape. And there’s so much creativity involved in their work to stay at the industry's bleeding edge—they’re constantly striving to use and advance the latest ML technologies.

“The MLDS team is so great to join because the team really cares about what they do—both within their roles and beyond,” Christa says. “They are great collaborators on initiatives outside of their day-to-day work, including a women’s MLDS group that meets for offsites and events, and maintain a strong partnership with our Inclusion and Diversity (I&D) team.”

As it grows, the MLDS team is looking for people comfortable learning on their own, who seek out ownership opportunities, and who are comfortable with change and ambiguity at times. They also want to hire folks who can bring their expertise to the team and teach each other new things.

The interview process: What to expect

The MLDS interview process involves a recruiter phone call, a live virtual pair programming session, a video call with your hiring manager, and a virtual onsite interview. 

During the recruiter call, we want to get to know you, understand what you’re looking for, discuss the role, and set expectations. 

For the pair programming interview with a Cash App engineer, we’re looking for fluency in the coding language you choose and to see how you communicate and collaborate. We want to see your debugging skills, how you speak to time complexity, and your capacity to devise and execute a working solution. 

Tip: Talk through your thought process! “We’re looking for how you work as a teammate, so share your questions, explain any shortcuts you take for time constraints, and remember to ask any questions—your interviewer is there to help you,” Christa says. 

To prepare for your pair programming interview, brush up on fundamentals like standard data structures and code organization. 

Next is a video call with your hiring manager. This is meant to be a conversational interview to understand your previous roles and the projects you’ve contributed to. 

Tip: Gather some questions for your hiring manager about the team, culture, and work we do. Showing your interest and curiosity can go a long way!

To prepare for your hiring manager video call, put together a brief bio about yourself with a focus on your recent experience. Consider why you're passionate about machine learning and/or data science and what appeals to you about the role. And while we appreciate team players, don't be afraid to use 'I' statements to demonstrate your impact and ownership. “Also, be honest about where you want to grow and improve—vulnerability is a selling point, not a weakness, for us,” Christa says. 

The final step in the interview process is the virtual onsite interview, which includes 4-5 interviews and a wrap-up conversation with your hiring manager. If you’re a Machine Learning Modeling candidate, you’ll have a couple of coding sessions and work through some case studies drawn from real-world problems on the ML team. If you’re a Machine Learning Infrastructure candidate, you can expect a mix of pair programming sessions, architecture and design whiteboarding interviews, and a past technical experience interview to understand your technical contributions to projects. If you’re interviewing for Product Data Science, you’ll have a SQL pairing interview, a couple of case studies, and a cross-functional interview. Finally, if you’re pursuing a Business Intelligence role, you can expect Python and SQL coding sessions, a data architecture interview, and a cross-functional interview.

Advice from the recruiter: How to ace your interview

“Communication is the most important part of these interviews,” Christa says. “Admit what you don’t know and be an expert in what you do know. Explain what you’re doing and why.”

And don’t forget to leverage your recruiter! After all, communicating doesn’t end with your interviews—remember to be clear and communicate with your recruiter, too. “I’m always very transparent and honest, and I appreciate that on the candidate’s end, too—it helps us get to the best results for everyone,” Christa says. If you have specific questions, your recruiter can find the answers for you, so don’t be afraid to ask anything that will make you feel more prepared and comfortable. 

Be honest about your expectations, compensation, and timeline—your recruiter is your advocate in this process.