She Got 2 Offers in 3 Months using Interview Query!

She Got 2 Offers in 3 Months using Interview Query!

Overview

Alma Chen is an ex-actuary-turned-data scientist who finished undergrad with dual Bachelor’s degrees in statistics and economics. After graduation, she worked as an Actuarial Analyst for almost four years. She then turned to Interview Query when she needed to prepare for her career change, and within three months she had two solid offers.

Since October 2023, she has been working as a Data Analyst on the legal compliance team at Lyft, after working as a Research Policy Analyst at DoorDash since August 2022.

We caught up with Alma to hear her story and the lessons she learned along the way.

Alma, What is Your Data Science Background?

After working as an Actuarial Analyst for four years, I was not very satisfied with my career trajectory in that field. I like working with data, and I like using insights to drive business decisions, but actuarial science is over-credentialed and the pay is comparatively low when compared to data analyst and data scientist roles. That’s when I decided to make the switch.

I quickly narrowed my search to data roles at tech companies, but I didn’t know much about their interview process compared to actuaries. It was easy to find generic resources online or on YouTube, but much harder to find specific interview preparation materials. That’s when I first stumbled upon Interview Query. The further I got into the field, the more I turned to Interview Query for guidance.

Describe Your Journey From Actuary To Lyft

When I was an Actuarial Analyst, I worked with a lot of data. In a way, it is like a Data Analyst type of job, but with very different objectives and tools. I didn’t use SQL at all in that job, and only a bit of R and Python. This background was not enough for me to feel anywhere near prepared for a data interview.

When I applied for my role at DoorDash, my first position after being an Actuarial Analyst, it was an entry-level job. Since they knew I didn’t have a lot of experience doing case studies or live coding, most of the questions were behavioral. By the time I got to Lyft however, I needed to be much better in those technical areas, and that’s when I got serious about exploring the resources on Interview Query.

I’m now a Data Analyst at Lyft, after starting at the beginning of October 2023. It’s been great. Transitioning from a traditional actuarial company to DoorDash was very difficult, but this second jump to another gig economy tech company has been much smoother.

In a nutshell, I’m doing policy research for their legal/compliance teams, and it’s very similar to the role at DoorDash that I previously held.

How Did Interview Query Help You Land a Job at Lyft?

I used Interview Query mostly for the case study questions, as I’ve found that there are a lot of basic SQL guides online, while case studies are harder to find.

For case studies, I like that on the Interview Query site there is a space to type out your answer, and then review other people’s responses as well. For case questions, there’s no right or wrong answer, just better frameworks, and ideas of how to solve the problem at hand. By viewing other answers, I can improve my line of thinking in the future.

Other positions I was interviewing for did let me know they would be asking about concepts in hypothesis testing and probability, and for those, I leaned on the Interview Query Learning Paths. These were a great refresher to my undergraduate studies and got me back into the vocabulary and flow of these kinds of questions.

Can You Describe Your Personal Interview Strategies that Could Help Others?

Actual Interview Practice

I think, honestly, the experience of interviewing for real jobs is itself the best practice for preparing for interviews. In order to keep my SQL abilities sharp for upcoming interviews, I would do about 45 to 60 minutes of SQL practice up to five days a week, and then on some of those days, I would record myself.

Recording & Self-Analysis

I would do a screen recording, because doing it live is very different from doing it by yourself, since it replicates some of the pressure and scrutiny of a real interview.

Recording yourself feels odd at first, but it is really helpful. I did a screen recording and a camera recording simultaneously. Then, because of those tools, I was forced to explain my work as I went along. I practiced my answers, talking through my thought process out loud. If I made a mistake, I couldn’t restart the entire question or the video. 

At the end of the day, recording myself forced me to catch my mistakes in real-time and make fixes to answers on the fly, just like in a live setting. I would also force myself to watch the videos for analysis. Even though it was a bit cringy, it was still a great exercise and helped me become aware of verbal ticks or crutches that I lean on. Overall, this was really helpful to improving my performance.

Applying for Multiple Positions to Practice Technical Interviews

I also applied for a lot of positions just to get technical interviews. For example, I knew that I did not want to work a remote-only job, but I applied to remote-only jobs so that I could get a technical interview. If they wanted to move me along the process, I would just say no. For case questions, I didn’t put as much effort into them as the technical questions. I would just practice for an hour a day, maybe two to three times a week.

Reading Books

Besides just online resources, I would read books too. I realize that when I read books, I become more eloquent and I’m better at explaining my thought process. It helps me not choke up.

No Prepping 24hrs Before

In college, I had a 24-hour rule for test-taking that I’ve brought into interviewing. I study up to the point that’s 24 hours before the test, and then in that last 24 hours, I’m not allowed to study at all. 

It’s hard not to break down and cram, so I have to force myself to watch a movie or something or go out with friends, and I would be calling them before interviews too to avoid the temptation.

I do not do any prep. I do not study. I do not read anything about the company. All of my preparation needs to be completed in a timely manner before the interview, which improves the quality of my research and clear-headedness at the moment. At its simplest level, I can walk into an interview knowing that I am ready.

Any Final Words of Advice for the Data Science Community?

The best approach to landing your dream role is to practice as much as possible. Practice by yourself, practice with others who are on the job hunt, and practice with established professionals.

This was especially helpful for me because I was coming from a position where I had no idea what the interview process would be like. Transitioning careers from one field to another can be really daunting, and if you just go it alone you won’t get feedback to improve.

Finally, get into as many real interview rooms as possible to hone your presence, both physically and in your answers. Supplements like mock interviews and answering questions on a place like Interview Query are very helpful, but nothing beats the real deal for getting better.