Genentech · Primly Community

Went through a full Genentech loop for a Senior Data Analyst role. Here's what actually mattered.

returner_ren · 5 replies

Background: I came back from a 2-year caregiving gap and Genentech was one of the companies that actually moved forward with me. I was nervous about the gap question but it turned out not to be the thing.

Here's how the rounds went:

Recruiter screen (30 min): pretty standard. They asked about my background, why Genentech specifically (have a real answer here, vague mission-speak falls flat), and confirmed I was okay with the hybrid requirement.

Technical phone screen (60 min): SQL heavy. Two problems, one relatively simple aggregation query and one involving a window function across clinical event data. Not fake data, they use domain-adjacent scenarios.

Panel day (half day, 4 conversations): one was a hiring manager values chat, one was a peer data scientist who dug into a past project end-to-end, one was a cross-functional stakeholder who wanted to know how I handle disagreement with researchers, and one was a short presentation of a past analysis.

What actually mattered: the cross-functional question. Genentech has a lot of scientists who think in different terms than business analysts. They wanted to know if I'd ever had to translate between those worlds without flattening nuance. Have a real story.

The gap question came up once, briefly, and my honest answer landed fine. They seemed more interested in whether I was ready than whether I'd been away.

5 replies

analyst_ana

the cross-functional story thing is so real. I bombed an early version of that question at a different biotech because I described 'translating for scientists' in kind of a condescending way. the framing matters a lot. you're not dumbing things down, you're finding shared vocabulary.

returner_ren

exactly. and the best signal I got was when the interviewer (a scientist herself) nodded when I said I'd asked the researcher what their mental model was before I tried to explain mine. that's the thing they're actually looking for.

sam_recovering

thank you for including the gap note. I've been dreading Genentech precisely because I assumed pharma/biotech would be more conservative about that. good to hear it wasn't the focus.

ds_dmitri

window function across clinical event data, that's interesting. is it survival analysis type stuff or more like just event sequencing? trying to figure out how much domain knowledge they expect you to come in with vs. learn on the job.

returner_ren

more event sequencing in my experience. they weren't testing survival analysis specifically, more whether you could think about time-ordered data carefully. you don't need pharma domain knowledge, but being able to reason about what 'before treatment' vs 'after treatment' means in a data context helps.