Only academics call it “industry”, but to everyone else it’s just called “work”

A bonfire hangout in San Diego: After listening to a grad friend and I bemoan the struggles of transitioning from academia into industry and our anxieties about which research loves (we thought) we’d need to give up, the person that I was dating¹ at the time quipped:

“You know, it’s only academics that call it industry. Everyone else just calls it work.”

At the time, this was hilarious to our burnt-out job-hunting brains. (Honestly, sometimes I worried that I was getting more stupid during the PhD.) My friend² and I still quote this to each other sometimes. Because now that my grad friends and I are now in capital I “Industry”, work is just work to us. Just, like academia was work when we were back in grad school.

If that last sentence was shocking in any way, feel free to skip my post Academia and industry aren’t that different (if you’re surprised-shocked) or Stay in academia if it’s your dream (if you’re offended-shocked).

---

Industry is not a monolith. Each company and team are bespoke in their language, skills, and cultures.

Why does this matter? After all, academic labs each have their own methodologies, conference application cycles, and interpersonal cultures. But at some point, you had to learn this difference when picking between academic fields and applying to different labs. Same logic here.

Job titles

Different companies have different titles for the same job. At my company, I’m called an Applied Scientist. At another company, I think that I might be called a Market Research, Research Scientist, Human Factors Scientist, Behavioral Researcher, Quantitative or Mixed-methods User Researcher, etc. With the integration of AI tools and vibe-coding prototypes, I also notice that recruiters reach out to me for Research Engineer, Post-training Research Engineer, Machine Learning Engineer, etc.

What’s more powerful than asking people to describe these different roles, is to

Describe your skillset and ideal goals to someone and ask that what this is called in their company

Bonus: Then ask if they can introduce you to anyone in this role.

Technical skills/tools

Depending on the company and specific team, what “quantitative” means can range from machine learning to google sheets to bespoke tools that a company has developed for its teams.

It’s not worth learning new technical skills & different tools until you know what they are. You can figure this out by networking with people. I wouldn’t recommend learning a bunch of new tools, when you could be spending that time conducting research for your PhD. Moreover, these days, it feels like new coding languages, new tools, or vibe-coding strategies through AI are popping up left and right.

If you were to ask me what I’d recommend as a starting place for my specific Applied Scientist role, I would recommend knowing your foundational skills in:

• Python & R (especially data visualization)
• Basic front-end web programming (HTML/CSS/Javascript)
• Command-line navigation
• and yes, vibe-coding — e.g., Claude, Cursor, ChatGPT

Even in the past year of my job, I’ve seen the specific tools change over time. But these specific foundational skills have been essential to my role so far.

Soft skills & personality fit

I’ve noticed that different companies value different soft skills and personalities. For example, while communication is always important, I’ve learned that almost everyone at Adobe picks up and convinced by visual information (e.g., visual examples, diagrams, plots) faster than other modalities.

For other companies (like Amazon), I’ve heard that people are valued for their writing abilities. So much so I’ve heard that writing workshops are a regular skills-building opportunity and that people often share a document at the beginning of a meeting, read it silently together for the first 5min, and then start the meeting. Note: I’ve not worked at Amazon before but have friends there, so take this with a grain of salt that I don’t have personal experience.

Knowing about how these soft skills are valued differently can help you figure out which companies are better suited for you and can help you showcase this during your interviews.

Another anecdote: One time I was networking with someone who was semi-criticizing Adobe and said “Adobe is kind of a weird tech company. They are tech people who wear scarves and berets.” I don’t wear berets (yet), but I was delighted to hear this because I am definitely a person who wears a scarf around the office. Networking helps to figure out these kinds of company culture and personality fits.

---

AI was not used to write, edit, or brainstorm this post. All mistakes and em dashes are my own.