Cheat Sheet: How to Choose a Startup as a Data Scientist

How I made the decision to join a startup coming from Big Tech

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Welcome to Scaling Down, a newsletter written by the team at Statsig for engineers and product builders who made the leap from Big Tech to a startup.

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How I approached joining a startup

After five years at Meta as a Staff Data Scientist, I took the leap and joined Statsig as their first Data Scientist.

At the time, I was excited by the idea of building something from scratch—but also nervous about leaving the security of Big Tech.

Four years later, it’s been a rocket ship, growing to 100+ employees, helping thousands of customers run >5k concurrent experiments while processing 1 trillion rows a day.

Through this journey, I’ve had the privilege of working with top-tier Data Scientists from companies like OpenAI, Atlassian, and Notion. This experience has been transformative, exciting, and pretty darn scary. I’m hoping that by sharing my experience, other data professionals can learn:

• Whether a startup is right for you

• What the tradeoffs are

• How to choose the right startup

While others may describe joining a startup as a leap of faith, an emotional, or an impulsive decision, for me, it was anything but. I approached this decision the same way I approach my work: thoughtful, data-driven, and grounded in experience.

Why consider a startup?

I loved working in Big Tech. It had generous compensation, world-class colleagues, impactful problems, and work-life balance.

Startups, however, are a different beast, and the rewards—both personal and professional—can be immense. Some benefits you can expect:

• Total Ownership: At a startup, you own your work in a way you do not at Big Tech. There isn’t a network of checks and balances. You may be the only expert at your company on a specific topic, and folks will look to you. The success of the company depends on you. You’re not a part of a machine any longer, and you’ll feel the immense weight and responsibility. But doing what’s right and landing quality work feels amazing.

• Speed: I hated long review cycles, endless alignment meetings (including the notorious “meeting before the meeting”), and layers of sign-offs across a nebulous organization. At Statsig, I learned that if something is important, just do it. If you need to make sure others are aware, you just walk over and have a quick conversation. If you need help, convince someone it’s important. No one is going to tell you, “but this isn’t on my roadmap.” You are in control of the pace of your work.

• Accelerated Growth: The pace of learning at a startup is unmatched. At Big Tech, you are rewarded for being an expert in a specific area; the whole company is full of experts. Startups, on the other hand, thrive on generalists. We have an unlimited set of problems but a limited bench of Data Scientists. People will work on critically important projects, even if they are outside of their core expertise. Successful individuals are undaunted by new problems and are fast at learning.

Choosing a good startup

I’ve turned down opportunities to join a few startups in my career. Some of them I regretted.

Over time, I’ve come to the conclusion that while startups are risky, they’re not equally risky. Some are destined to succeed, while others are headed for failure. I’m also convinced that success is predictable (to a significant degree), and there are traits you can identify before joining.

Here are the traits I looked for when joining Statsig:

• Team Quality: Investors know this…the caliber of the founding team is absolutely critical. A great founding team with a flawed idea can pivot to success. Conversely, a mediocre team with a great idea will get crushed by competitors. Look up the founders’ track records. Do they have the “Midas Touch”? I was lucky because I had previously worked with Statsig’s founding team and knew they were talented, execution-focused, and just plain fun to build with. But you can scour your network and do your research to find people who can vouch for them.

• Industry and Growth Potential: Is the company solving an important problem in a growing industry? Does the industry have only a few critical competitors? The best startups operate in markets that are evolving and expanding.

• Secret Sauce: Does the company have an unfair advantage? Will they be able to win a dogfight against fierce competitors?

If you’re considering joining a more established startup (Series B+), you should also consider:

• Company Trajectory: Is the company gaining customers, hiring great people, and securing funding? A growing company means more opportunities for you.

• Reputation of Employees: The employees will be critical in defining the company’s future. If you respect and admire the team, it’s a strong sign. One trick I’ve found useful: talk to former employees. They’ll give you an unfiltered view of the company’s trajectory, leadership, and culture.

• Makeup of the Team: If you’re a junior employee, you’ll want to make sure there’s mentorship and support from folks you respect. The good news: startups need you to grow into a productive team member, and folks are invested in your success. I’ve unfortunately found that at Big Tech, mentorship is often a checkbox for someone trying to get promoted, and mentees are often paired with mentors who don’t fully understand their work.

Picking a good startup is more than just a job choice—it’s an investment in your future. Being part of tomorrow’s next big thing can be a badge of honor on your resume. It shows you helped build something great.

Closing thoughts

Regardless of your experience, joining a startup can be the best career decision you make. The learning, ownership, and experience you get can have a profound impact on your career. But make sure you’re comfortable with the risk and tradeoffs.

Not all startups are created equal—so do your homework. The right one won’t just be a job; it’ll shape your career in ways Big Tech never could.

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