Spring Health Data Scientist Interview Questions
& Process

First up was a quick 15-minute call with a recruiter to go over my resume and ask some basic behavioral questions. Then, I had a 1-hour live SQL technical interview where I had to write code, but not execute it. The interviewer was really interactive, making it feel like a team effort. Finally, a 30-minute behavioral interview with the hiring manager. It felt a bit rushed, and they mostly asked about my technical background and my interest in Spring Health.

Had a first chat with the recruiter about my background and what the job involves. Then there was a technical screen, which was a mix of SQL and product design questions. After that, I went through a confusing 'loop' where several interviews were scheduled at the same time. It was the hiring manager, then ML team folks, and then stakeholders. The whole thing felt a bit disorganized because they scheduled a full panel before the hiring manager even checked my skills and profile. The process also required a lot of time commitment upfront for multiple interviews. The ML part was a bit of a letdown, felt like it was just copying other big tech companies' formats and I wasn't sure if the interviewer even knew the answers or how the questions truly evaluated if I could perform well at Spring Health. The recruiting team was super professional and quick to respond, but the hiring team seemed to lack a clear vision for their product goals and future roadmap.

The interview process took about 4.5 to 5 hours, starting with a recruiter call. Then there was a round focused on SQL and 'data modeling' along with a 'tell me about a project' question. Next, they had me do a machine learning case study, also with a 'tell me about a project' component. This was followed by a meeting with the hiring manager and another with a product manager partner. They mentioned I might meet the CPO or another founder, but I didn't reach that stage. I generally liked the people I met, though I felt disrespected by some. During my ML case, one interviewer was clearly on Slack and rudely stated I lied about my accomplishments when he misunderstood my causal ML model explanation. This interviewer and another were 3-5 years less experienced than me and lacked production ML experience, yet acted like they knew more. They did call back to say they weren't moving forward, citing company policy against feedback, and then told me they wanted to consider me for future roles and to reach out, but then reposted the job two weeks later! The interview questions felt a bit silly and not optimized for minimizing False Positives or False Negatives; they asked about restaurants instead of a problem space like mental health to gauge thought process. Some interviews spent over 5 minutes on weekend plans but rushed the technical parts. I suspect they recruit based on personality, healthcare experience, and tolerance for 60-hour weeks with menial tasks, and that the company has changing priorities with sales/accounts constantly asking for data pulls. This interviewer on Slack was probably swamped.