Rounding up career decade 1 and spent quite a bit of time in consulting/MBB and venture building. Transitioned to Product Strategy in Tech but stagnating so looking at Group PM or Head of Product Analytics Current product org has 15-20 PMs/Leads but no GPM. Product analytics is 0 people and completely untouched capability in the company. So I’m Leaning towards Product Analytics — inspiration is Crystal Widjaja Regardless of the position, I expect a significant ramp up https://www.linkedin.com/in/crystalwidjaja TC: 160k (in EU) YoE: 10 (4 in Product)
Have spent 6 years in data space. Almost 3+in product analytics. Product Analytics is a little difficult without understanding the technicalities of data. Especially if you’re building it from the ground 0. Analytics team is the bridge between data engineering and product teams. You have your strength with the product team already but might need some exposure to data technicalities as well. It looks rosy but it’s really difficult to scope out the projects and set expectations even with a data background.
Agreed. Being the first of any role is really difficult as it is and much more so if you have no experience to begin with
Even after 5 years of BI, it's still extremely tough to scope and estimate projects.
No TC?
TC updated
I don’t see numbers.
Data roles are the absolute worst - zero ownership. I was happy with data roles initially but then you become a periphery in the grander scheme things happening at the org and you dislike it. It also makes your personality boring - this is a big thing to consider. Group PM > Head of PA
They’re not the worst. But it’s hard to find an org where data teams are well respected. Plus it’s even more rare to find a good data leader. They’re very fulfilling roles if you get the right projects. You can actually help with the strategic decisions. But then again these are a lot of ifs.
Also +1 on Group PM > Head of PA Head of PA is way more work than Group PM and it’s not as rewarding.
I’m curious, are you being offered these roles or are you looking to move into these role? These are both L7+ roles in tech and are extremely competitive without the relevant experience. Both have some overlap to product strategy but PM more than analytics. To jump right into a Group PM role without being a PM before is almost unheard of though. If you don’t know experimentation and don’t have a statistics background then I would go with PM. It also has higher upwards trajectory.
I took statistics 101 once in high school and once in college. Let’s gooooo
Jokes aside, yea looking at those director roles. I have 4 YOE of PM experience prior but it wasn’t at large tech so it’s need still some brushing up
Crystal is amazing.
If you get into product analytics unless you already know what to do or you’re really good at leveraging and building the team fast do you’ll probably get layered soon pretty fast as well. Domain knowledge is a massive difference between knowing and delivering, especially in DS.
Don't make me tap the sign 👆
TC is updated
Transition to product strategy in tech - what role is that?
Creating and leading strategy for the portfolio
What’s the role called?
GPM is a role offered by midsized to large companies. Without prior PM experience, are you getting any success with interview calls so far?
Tech Industry
16h
1540
Why doesn't OpenAI offshore and reduce expense by 80%
Tech Industry
3d
40530
What happens when most of your team is Indian?
India
Yesterday
1443
Ideal indian parents
Tech Industry
7h
201
Is Israel getting bad PR the reason for banning tik tok?
Software Engineering Career
15h
547
Do Tech leads make more than Engineering Manager?
Do you have any ds experience? If you don’t, I think you’ll have trouble leading this team. PM is general has better career progression and pay.
structured thinking is core to top tier consulting so I can structure what end insights and analysis that might be needed but actual execution of DS/DA at massive scale is not my forte. i can build a team to execute so main thing is ensuring that the right direction is set
Right, I think making the technical trade offs is the difficult part. For example how would you scale experimentation and instrumentation to ensure your org has the correct tooling set up to succeed? Is there sufficient data engineering resources to make use of an analytics org? Not saying you can’t do it, but it really helps performing that function when trying to build out of a team for it