• Dawn Choo took a 40% pay cut to pivot from finance to a tech job at Amazon.
• Choo's transition involved moving from a quant role at Bank of America to a business analyst role.
• Her career shift eventually led to her dream job at Meta, after applying around seven times.

This as-told-to essay is based on a conversation with Dawn Choo, the 34-year-old founder of Interview Master, based in Chattanooga, Tennessee. Her identity, employment history, and salary have been verified by Business Insider. This story has been edited for length and clarity.

I interned at Facebook in college, and my dream was to get a data scientist job at Instagram — but I didn't get an offer.

I took the first offer I got in college because I had interviewed so many times at so many different places. Finally, I got a finance offer from Bank of America, and I took it because I needed a job to stay in the country, even if it wasn't exactly the industry I wanted.

It was a quant role, but it wasn't very data-heavy. I did backend work, like building models to help predict if companies that took a loan from us were going to default on the loan. I was there for three and a half years, but I started applying for tech jobs about a year and a half into the job.

Again, I tried so many times. I was not the best at interviewing. I applied to about 100 places, interviewed at maybe 10, and then finally I got an Amazon offer in 2017.

I took a roughly 40% pay cut and a step back in my career

The Amazon job was for a business analyst role, and it was a really big pivot.

When I applied, I knew I was taking a step back in my career given the scope of work, but I didn't realize I would be taking a roughly 40% pay cut.

I was living in New York City in a one-bedroom with a roommate, so that 40% really made a big difference.

Despite what felt like moving backward, I could see the upsides of taking the job. Amazon's a big company, and I knew it was a step toward where I wanted to go. I had to make some adjustments, like eating at home more. But I also felt like it was a step back in my career because I suddenly stepped into a service-desk role.

I didn't love the work I did at Bank of America either, but at least I was building models and writing extensive documentation. At Amazon, I felt like I wasn't really learning much, and many times, I wondered, "Why did I take this pay cut? Why did I make this transition? Should I just go back?"

At times, it didn't feel like the right move, but I recognized that I had agency over that decision. I chose to be there, and it was a privilege for me to be able to make that choice.

Things got better

The upside of the work being very repetitive and simple was that I could automate it. The automation project started as a pet project — I randomly came up with the idea and pitched it to an executive. He loved it so much and kept pushing me to do it that eventually, I did.

I was promoted from business analyst to business intelligence engineer. What was initially my site tech project became a full-staff team of five business intelligence engineers.

I worked for Amazon for two years before getting my dream job as a data scientist at Instagram.

I interviewed at Meta so many times previously. After my internship, I applied about seven times and interviewed maybe four or five times. I almost canceled my final round of interviews because I couldn't get rejected again.

I think my experience working in tech and product changed my application. I also had a lot more leadership experience since I spearheaded a project. Plus, I matured around interviewing and presenting myself.

I worked at Instagram for about three years and three months. The office was beautiful. The people I worked with were incredible and made me feel challenged. I made a lot of good friends, and we went through COVID together. They were part of my pod.

Bets take time to pay off

For others thinking about making a career transition, I would say take the pay cut if you have to. I've always feared regret more than failure. I knew if I didn't take the Amazon job, I would be upset for not betting on myself.

It's also important to recognize that some of these bets take a long time to pay out. It took me two years, which wasn't that long, but I know other people where it took longer to get that payout.

Sometimes, even after the payout, you see other people in your situation and you think, "Wow, this person got this data science job at Facebook right out of college." So, at that point, I was about eight years older than this person doing the exact same thing. And it didn't feel great. So, maybe don't compare yourself to other people.

I will always say take the bet on yourself — and I'm doing it again. I pretty much took a 100% pay cut this time. I went from my comfy corporate job with insurance, travel perks, and stability to work for myself, and I hope the payout will come soon.

• Mike Crabtree, a data engineering director at Ford, took over 25 online courses to skill up.
• He said learning new skills is crucial to protecting your job amid recession fears.
• Online courses improve your problem-solving and communication skills, applicable in multiple fields.

This as-told-to story is based on a conversation with Mike Crabtree, the Director of Data Engineering at Ford. The following has been edited for length and clarity.

In 2008, I had just received my associate's degree in industrial mechanics and electronics engineering. Then, the recession flooded the labor market.

In a crowded field, my degree and resume — mostly retail experience — didn't stand out as much to employers.

As I pursued a bachelor's in business and computer information systems, I knew I needed to differentiate myself more. I started taking paid online courses from platforms like Coursera, edX, and Udacity, earning certifications in everything from business analytics to leadership skills that I shared on my LinkedIn.

While I didn't major in data science, I took supplemental online classes that helped me stand out and pivot into the field. Ford reached out months after I graduated in 2016. The company hired me as a data scientist that November, a role I stayed in for five years before becoming the manager of a data engineering team. After leaving Ford to work for a data-specific organization, I returned in 2023 and eventually became the director of data engineering.

These days, the job market is a little tougher to break into, let alone stay in. Some people are looking to recession-proof their jobs amid concerns of AI disruption and economic uncertainty.

My experience taught me that the key is to keep learning. By choosing challenging online courses, I tapped into skills I never used before, from technical ones like programming to soft skills that helped me grow as a manager. Taking classes in everything from entrepreneurship to self-driving car engineering also signaled to managers that I was proactive and willing to learn — qualities that are important for feeling secure at a job or getting a promotion.

Here are three ways to recession-proof your job as much as you can — or land a more stable one.

Find your gaps

To feel like you're in good standing at your job or that you're prepared for upcoming interviews, you need to be as well-rounded as possible. If you're incredibly self-aware, you might already know your skill gaps. Personally, I didn't learn mine until I started challenging myself with online courses.

Because statistics and the scientific method are foundational in data science, I took a statistics course. I got stumped on probability and had to improve my understanding before I could move forward. Later, I took a machine learning class and realized that linear algebra wasn't my strong suit. In addition to learning the needed technical skills from those courses, I also learned how to spot my weaknesses — and take action to fix them by studying more.

This can apply to all fields. You might be a manager, for example, and need more leadership training. If your job doesn't directly offer many opportunities to push yourself outside your comfort zone, courses can help you quickly spot what you struggle with.

Grow your problem-solving skills

Being able to think critically, solve problems, and lean into your intuition makes you a more valued team member.

The good news is you don't need to stuff your brain with as many facts or programming techniques as you think. It's more important to be able to assess direction, build business acumen, and make confident decisions.

You might know how to build a linear model as well as AI does. But when you can just look that up, what matters more is realizing that a linear model isn't the best solution to a problem in the first place.

One way I beefed up my critical thinking skills was by taking a course in quantum computing taught by IBM, which heavily involved physics — something I wasn't an expert in at all. It taught me to think quickly and wrap my head around a lot of conceptual topics. I went in thinking I was learning one skill, but I left learning four.

Be communicative

Forming strong workplace relationships is important, especially in a tough job climate. After I worked at Ford as a data scientist, I left for a managerial role at a data company. When I exited that job, some old coworkers at Ford started reaching out the moment they knew I was back on the market.

Throughout my career, I've seen many brilliant technical professionals struggle to move up — not because they're mean or ornery, but because they're super quiet and keep their heads down. Because they weren't assertive enough, people didn't know much about them.

In my own career, I've taken public speaking courses to improve my communication and confidence. Beyond simply speaking up, it's also crucial to be able to share your suggestions in a clear and approachable way. This is especially true if your job is highly technical.

You can be the smartest person in the room, but if no one knows your name or understands your ideas, it doesn't really matter. Bridging that gap by building up your soft skills is the best way to set yourself up for success.