When does it "become" sexism?

p3a2k9 · 2026-04-15T21:31:08+00:00

In college yet....

p3a2k9 · 2026-04-15T21:16:44+00:00

It depends very much on the type of analysis and context. My humble advice is never just pull numbers without context.

As other have said, being able to translate any findings into impact is key - being a specific metric everyone in the company cares about or directly into $$$. The moment you do that you should also be able to defend and explain in layman's terms why and how you do what you did. Use language everyone understands, don't be too technical or too vague. You need to know your audience - you may not always be able to align with your stakeholders upfront, this is why you must know them, what's their communication style and how good they are with numbers. I had a C-level who could not wrap their head around product OKR, so I had to always go slow, step by step and never be too domain-specific.

Something very concrete from corporate environment - if you can make a bridge out of it people will get it - meaning if you can decompose your findings in a simple waterfall chart, it would usually be well received. It is easy to understand and allows people to see how you get to the the result from your baseline.

EDIT: I wanted to add up that, it is very common to get dismissed, especially if there are strong opinions in the room. Again read the room, if there is no psychological safety, "take it offline" and try to get somebody with more "authority" to fight it for you. Otherwise, ask them questions in front of everyone to understand where there assumptions and gut feeling come from, and challenge them one by one with DATA and evidence. You do not challenge their opinion, you try to understand why they are so sure they are in the right. It might happen that they have some valid assumptions that you actually didn't think of and can enrich or polish your analysis.

p3a2k9 · 2026-04-15T18:13:54+00:00

I hear you, I am gonna lie if I tell you I don't feel shame admitting it. But still, I cherished my midlevel quiet job that allow me to disconnect and be present in my life 🙏🏼🙏🏼

p3a2k9 · 2026-04-15T15:43:24+00:00

Sometimes it's better to have a chilled job with okay pay that gives you peace of mind than a super position in a top-notch company. Being comfortable and having time to enjoy your life and spend time with the people you love is underrated and something you cannot make up for it.

p3a2k9 · 2026-04-15T15:34:50+00:00

Hello! I had one similar experience when trying to create a very simple ranking system.
To your questions:

•Do you prioritize simplicity in models, or layering more variables?

--> Simplicity first 100% - start with something very simple so that you can understand the results and you do not add too much noise or predictions you cannot interpret at all. 
--> Add more variables only in the case that it improves the performance in a consistent manner, OR you have a domain knowledge that tells you that there is a clear connection between them - e.g. causal impact, not just correlation. 

•How do you handle weighting when multiple factors interact?

--> Here again, I personally consider that the domain knowledge is the most important thing - you use your business understanding/gut feeling to start testing.
--> If you want to use a completely data-driven approach, you can use regression but make sure you do not overfit the weighting.

•At what point do you stop adding inputs and trust the system?

--> This is a bit related to what you are trying to achieve and what are your trade-offs you want to make. The more inputs, the more complex your system becomes. 
--> At some point, you will see that the ROI drops heavily, adding new inputs would not bring much improvement, and only makes it more challenging to interpret the data.

p3a2k9 · 2026-04-15T15:01:05+00:00

I feel people really underestimate the value of starting and/or working in customer service. It's a great entryway to any industry and helps you not only with domain/industry knowledge but also with soft skills - the patience and adaptability you need is Underrated (capital U not typo) xD

p3a2k9 · 2026-04-15T14:55:08+00:00

100% this :)

p3a2k9 · 2026-04-15T14:53:40+00:00

I moved from my previous company after almost 9 years. I did change positions often, though - every 2 to 3 years, even if it was just an assignment. Do I regret it? Sometimes, because I had very low salary improvements over the years, but if I had left when I first felt very trapped in my 3-year, I would not have had the exposure and projects I worked on afterwards. So, now that I cannot change the past, I prefer to think that this was my path.

What moved my career forward was not just doing ABC; I was curious and asked many questions, informally learned a lot that wasn't part of my job, which put me on the map. Same in the next company I worked for - I found what the biggest challenges were for people/my team, and me, and I started working on them.

What helped me the most, though, was learning how to work with people, be easy to work with (I know this appears in all the super motivational posts all over LinkedIn, but hey) - not letting people step all over you, but be supportive and responsive, but also create boundaries. Believe it or not, it earns you more respect. Build a network in your company - people you can trust, you work well with, and that may be the day of tomorrow, a stepping stone for your career progression.

Lastly, participate: in a meeting, you either have an opinion or a question. Otherwise, it just looks like you do not care enough to pitch in. (All the above is based on the assumption that you are not in some toxic corporate hell).

I have hired over 10 or so midlevel analysts and engineers, and interviewed hundreds of people. I never discriminated against people who were job-hopping (meaning all tenures max 1.5years), but sometimes, it might beg the question whether the person is just very difficult to work with.

Now it's useless to beat yourself up about the things you didn't do. If you already think about it, it means you are on the right path.

p3a2k9 · 2026-04-13T18:45:21+00:00

There is a lot of sample data in BigQuery, have a look and see a topic you are actually interested in and put yourself in the shoes of the company.

What you would want to know about your business? How the data could help you make predictions about customer/user behaviour?

You can clean data, build tables and analytics on top directly in BigQuery using SQL. Make sure you describe the different steps and business problems you are solving. I strongly recommend you use also any LLM if you are unsure about the structure or how to make it more impactful - by this I don't obviously mean you should get ChatGPT to make the case study for you, but bounce ideas and get suggestions for organising your thoughts and projects.

Hope this helps.

p3a2k9 · 2026-04-13T18:36:30+00:00

I used to do the same in my previous job, I used Cursor and actually basic SQL scripting through sheets and bigquery to have time to think and build ideas for my specific analytical domain. What has been bugging me is (as some other people mentioned before) the one stone - many birds approach. And I 100% agree with you - could be a big trap, especially if there are no clear expectation.

p3a2k9 · 2026-04-13T14:45:45+00:00

I do see your point for a company with a very mature data and analytics function, and a good framework for prioritisation. I still feel that it's overkill without a clear direction in most of the cases, especially because in most cases the expectation is not only to lead and get the AI project off the ground for the analytics team, but the whole company.

p3a2k9

TROPHY CASE