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I’ve been trying to get into the top tier Associate Product Marketing Manager position Google for some time now for just an interview and I feel like business majors somehow have such a stronger chance in getting interviewed especially my business school and I feel really discouraged as an Econ Major and I have a lot of marketing experience that I’ve built over the years. Are there any non-business majors in the tech realm in non technical positions at Google that can advise me?
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Well your title says director, maybe they meant they feel like you haven’t “rolled up your sleeves” much recently. I’m spitballing here but trying to help. Also why would you want to be “technical” post director level? I’d rather stay in “management” lol
Changing industries for higher earning potential and I’m getting bored. I’m not even close to retirement and don’t really care about the title or money.
I've seen tons of people who have 15+ years of experience, a master's degree, and a dictionary of skills on their resume. Then you find out they've been more or less managing people for the last 8 years and aren't exactly a very technical "doer". This tends to happen when people settle into industry and then later try to consult again; their best skills are usually deprecated.
Yeah Slalom 1, I hear you. Apologies for misreading your first comment. On second thoughts, it’s a fair comment.
“Did not know some obscure function that I like to get hung up about”
This one time I was asked at an interview for an associate position if I had ever used any theoretical mathematical models for any of my clients. I said that I did not have the chance yet and asked if HE had used any theoretical mathematical models for his clients as I was curious about the use case.
He said no he had not. He rejected my candidacy for “not having appropriate knowledge for a data analyst”.
The most complex algorithm I have ever seen was from a developer who was patching up work done over time and not documented.
In terms of actual complexity, the most complex I have yet to see in production is a graph based algorithm for anomaly detection. I have yet to see anyone break out their physics books. I am glad I got rejected as I would have ended up working for that person if I made it through that interview.
My guess is that they perceive lack of technical depth. That might include system design, algorithms/complexity, sizing/cost, and possibly technical leadership (leading a team, thought leadership, managing up, etc.). It could also be understanding of how frameworks and libraries work underneath the hood (great for optimization and solving serious build issues/constraints).
Not sure what you were interviewing for as that will determine what technical experience they were actually looking for.
Interviewing for analytics roles outside my current company/industry.
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It could mean you didn’t get specific enough about the specific method you used in the tool, esp the whole process from start to finish. If it sounds like you were giving too “high-level” of an overview then it could sound like you were faking it.
There were also prob specific technical words you were meant to use when you made your points, and if the examples you gave didn’t use those words then you’re considered “not technical enough”.
Also if you said “I didn’t do this but worked with/managed a team who did this specific method” then obv you’re gonna be called “not technical enough”.
What if I TRAINED the team how to use the technical tools?
Also, for my case there was a coding round which I passed. Hence, I clearly can do the technical part.
Personal opinion: Master's degrees have a negative effect on your resume. Most people can get solid industry jobs out of undergrad, and those who actually want to learn more about a field do a PhD. People who couldn't do either pay tens of thousands of dollars for a masters.
Not sure why some are commenting having a MS is not technical unless they are talking about cash cow Boot Camp stuff with no thesis. I assure you if someone completes a MS in engineering and defended a thesis, that person is very likely technical. It’s not equivalent to taking “some online course” and if they is what the interviewer thinks, that interviewer is incompetent.
I've been 'not technical enough' and I've probably called people that, although I might not use that specific language. I had more coding/data engineering experience and they were looking for ML. When I've expressed that sentiment about someone, I didn't think the interview supported what they had on their resume - like, I wasn't convinced they could actually show up and write code that was clean, readable, testable, and would run. Maybe I saw gaps in terms of theory - like, they weren't familiar with data structures.
And I have interviewed people who had experience teaching a particular language/being the sme for their team, and who I didn't think were capable in that language. There are just very different standards for what capability means across teams and employers.
Thank you for the tips.
I’m already half thinking to myself: at this stage I might as well just sit on my hands and collect this director salary while continuously learning more during my free time
You probably threaten the current team. I have this happen to me all the time.
I lead a team, we are very productive, I don’t have to code much - puts me at a significant disadvantage for coding tests - which are not predictive of performance.
You probably are too good, at your level, at making things seem easy to you.
Avoid the idiot hiring teams that don’t understand what you do - as frustrating as that Is. I know interviewing absolutely blows.
I don't think you need to be able to pass a FAANG-style algorithms test to be a working data scientist. But passing a test of your coding skills for a data scientist job is about as close to testing whether you can do the job as you'll get for any professional job. I love when someone gives me a coding test because I like coding, I have put the work into improving at it, and I want coworkers who feel similarly. The one time we hired someone who talked well but didn't do well with coding (because we were desperate), he could, in fact, not code.