I’m curious how long everyone thinks is too long to stay at one company and how that would impact your prospects when applying elsewhere. I’ve seen posts on various platforms where people say the average is ~3 years.
I’ve been at my company for just shy of 7 years and am beginning to worry it will impact my prospects when I re-enter the job market. I didn’t start in Product though, so I’m hoping that will show some growth; 1.5 years in customer support, ~2 as a Product Analyst, 1 as an Associate PM, 2+ as a PM.
If the person is stuck in the same level/role for a long time at one company, I see that as a red flag. If they have been at the same company for a long time, but have been growing in their career and/or scope of work, I see it as a positive.
On the flip side, if I see someone grow from a graphic designer, into a product manager, into a director of product management all within the same company then I’m going to be a little wary of their expertise/experience.
I’ve seen lots of folks stay places for 5+ years and get promoted because they were who was left when the qualified people departed and/or they knew the politics of the place well enough to nab promotions.
How would you account for the maturity/growth of the product/company? If the company isn’t rapidly growing or the product is mature, then you won’t see the PM team growing. So that means no promotions or changes in responsibility. And when a product doesn’t have the growth momentum nor resources of a rapidly growing company, the PM has a really challenging role.
Having recently joined a new company after committing to a place for 4 years, I feel stupid to have put up with the toxic leaders for that long. People leave for all sorts of reasons. We all have a combination of skills. Roles come in a variety of flavors. Some may require more focus in one industry than another. I interviewed at a place we both sorts of recognized wasn’t a fit considering their needs. Another I was shocked they didn’t hire and they basically revealed they were planning on just hiring internally.
Anyway, I think the notion of planning a career based on how long to be at a place could vary and how we judge candidates can also vary. I will say that sticking through the downs of a company sucked but was a huge learning experience. Also, you form bonds with people that cannot be described on a resume (even with toxic leaders). It also teaches you what you really want or really are good at. Don’t take career planning too seriously. Take charge of life but also learn to embrace the curves, uncertainty, and unexpected punches. They’re as many blessings as burdens.
Good question- as a follow-up anyone working on AI/ML-driven products and knows what Sr. PMs for such products should have in their skills portfolio?
I’m currently creating a lead generation and lead qualification solution for a VC firm and am upgrading my coding and DS skills as well as quant finance skillsets.
@PriyaVarma
My 2 cents:
It depends on the company.
Bigger companies such as FB, Uber have strong Data Science functions.Here, PM focuses primarily on user/ business outcomes, ask smart questions to DS, understand the user impact of false +ve/ -ve. Understanding of precision, recall etc. is good to have but not the primary expectation as DS will analyze the results mostly.
Smaller/ Leaner companies (like my previous venture), you might want to get into the analysis yourselves. However, I haven’t see the PM to expect to code heavily but PM should be able to set up/ configure a model, interpret the results, suggest improvements etc. However, the core “job” for PM is still business outcomes.
In very small startup/ with no dedicated ML, DS. Well you do whatever it takes
The most important skill across all archetype IMO is ability to define clear goals, interpret results and its impact to the goals you have set up.
Thanks, Prashant. I like that breakdown by company size. I won’t call us a small but we are not a big company either. We are somewhere in the middle and there is some urgency on our end so I am right now in a ‘do what it takes mindset’.
Beyond that, a part of me wants to dive into ML because it is fun Another part wants to do what you said - define clear goals, find the most efficient way to get it done, measure results, and do it again.
