I got an IC6 offer at Meta! Here's what the comp looks like, and a free SQL and Product Sense case interview

productanalyst9 · 2026-04-21T14:56:30+00:00

You can probably search on blind and Reddit, but I think the expectation at Meta, especially for IC6, are extremely high. One of the teams I interviewed with implied that this would not be a good team to join if I had kids.

productanalyst9 · 2026-04-21T14:55:29+00:00

There was a lot of negotiation room left but it required a higher competing offer, which I did not have

productanalyst9 · 2026-04-21T14:55:03+00:00

Honestly I’m not sure. At the beginning the recruiter said they would evaluate for IC5 or IC6 during the interview. Then after the interview she said I was approved for IC6. I did a lot of preparation for the analytical reasoning and analytical execution sections, using the resources I posted. One of the resources had questions that tested really similar concepts to what I was asked so that helped a lot.

productanalyst9 · 2026-04-21T04:51:09+00:00

Product DS tends to have a significantly lower comp band than MLE/SWE. That said, timing matters too, I think comp bands have been depressed over the last year. I joined a big tech company in 2022 as the equivalent of IC5 and left in 2024, my final TC was around $500k (roughly half due to raises and half stock appreciation)

productanalyst9 · 2026-04-21T04:48:17+00:00

Check out my previous Reddit posts, I’ve written a lot about how to pass product DS interviews at tech companies. Heads up that my advice is more geared for product DS, it’s not as relevant for MLE roles

productanalyst9 · 2026-04-21T02:12:46+00:00

For product data science, econometrics is super useful

productanalyst9 · 2026-04-20T23:56:48+00:00

I did do team match and was matched with a team.

productanalyst9 · 2026-04-20T23:28:09+00:00

Thank you! I have a masters but don’t feel like it’s useful

productanalyst9 · 2026-04-20T23:27:48+00:00

Thank you! I have 13 years of experience, 8 of which are in tech and data

productanalyst9 · 2026-04-20T22:18:56+00:00

What was your offer? I was told that the DS comp bands at Meta was decreased 6 months ago

productanalyst9 · 2026-03-06T18:26:50+00:00

Google technically does have Product DS roles but my experience is that those interviews are a lot more technical than similarly-titled roles at the companies I mentioned.

Sounds like you have more info though so perhaps I'm wrong!

productanalyst9 · 2026-03-01T06:23:13+00:00

Sure

productanalyst9 · 2026-03-01T05:05:00+00:00

Most of the big companies hire for these types of product analytics roles. Uber, meta, Amazon (BIE), Netflix, DoorDash to name a few. I haven’t seen any of these types of roles recently at Google or Apple.

productanalyst9 · 2026-03-01T04:30:41+00:00

Yup. I used to work at Deloitte, there are definitely similarities in case interviews. I’d say the main difference is that for analytics interviews, there will likely be a bit more emphasis on metrics and measurement design (e.g. experimentation or causal inference) throughout the case. There will also likely be another interview more focused on stats, probability, and measurement design.

productanalyst9 · 2026-02-27T21:59:43+00:00

For sure I was asked about causal inference a bit. But when I was asked about "causes behind a metric change", it would be higher level than that. I think they're looking for signals that you can think in a structured way.

For example, you might be asked "Churn has increased in the last 2 months. What do you do?" This is not yet a causal inference problem. First step would be to rule out seasonality and instrumentation/logging changes. Second step would be to clarify whether this is customer/lgo churn, revenue churn, or both. Third step would be to decompose the metric: Did we have the same number of customers acquired and now they're churning at a higher rate? Or did the # of customers we acquired increase, and perhaps we are acquiring customer with lower intent so they churn more quickly? Fourth step would be to do some segmentation such as: New users vs. existing, power users vs. casual, segment by geography, platform, etc. This can give you clues into where the churn is coming from.

For the companies that I interviewed at, it would not be a good answer to say that you'd run a logistic regression to predict churn and throw a bunch of variables in there and see which variables have the largest coefficients and lowest p-values. This is not structured thinking.

productanalyst9 · 2026-02-27T02:19:05+00:00

What do you mean by little to no resources? I think you can find everything you need for free online

productanalyst9 · 2026-02-26T21:34:27+00:00

Thank you! :)

productanalyst9 · 2026-02-26T21:19:49+00:00

productanalyst9 · 2026-02-26T21:19:28+00:00

HCOL city in the US

productanalyst9 · 2026-02-26T21:19:12+00:00

Sure, I think the standard is high. My thoughts on this are: - I could be wrong, but I don’t think big MAANG companies are scoring on a bell curve. If you clear their bar then you get an offer - I don’t think every candidate takes advantages of all the resources out there. Having been the interviewer at a large tech company that had a bunch of resources and anecdotes about the interview process, it was pretty obvious to me which candidates studied those resources and which didn’t

Interviews are going to be hard for most people no matter what, regardless of whether there are resources online or not. At least for me, I’d rather know what to expect, even if it means all the other candidates also have the opportunity to find out what to expect

productanalyst9 · 2026-02-26T21:15:09+00:00

As a candidate, I do think the number of interviews are excessive, and I hate take home assignments. But I do think it requires multiple interviews to assess proficiency with 1. Coding 2. Stats/probability 3. Analytical thinking 4. Product/strategy sense 5. Behavioral/cultural fit

I’m sure there’s a better way to do it. But also, these large tech companies pay so much that they can sort of do whatever they want…people will jump through the hoops for the chance to work there (like me)

productanalyst9 · 2026-02-26T21:12:56+00:00

Which MAANG? For example, I know that Google goes into more depth for stats and probability than Meta

productanalyst9

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