Walk me through a past data science project.

"A sourcer had been nudging me on LinkedIn for a while, so I never did a normal recruiter screen. Once I sent my resume, two hiring managers in the same Siri AI/ML org wanted to talk, so Apple ran one combined process for both EPM roles instead of making me do two separate loops. I did two hiring manager screens, then a joint onsite with a data science manager, an ML engineering manager, another behavioral round with one of the hiring managers, and a final conversation with a very senior engineering leader. The whole thing felt extremely team-dependent and very niche, especially the ML metrics parts, which is what made it different from more generic big-tech TPM loops. I finished in early December and got rejected."

"I got reached out to on LinkedIn and went through the full loop for a Senior Data Scientist role in San Francisco, targeting around L5. The process was recruiter screen, a 48-hour take-home data challenge, a one-hour technical review of that challenge plus AI-code debugging, a hiring manager screen on one of my past projects, and then a four-interview final panel. Overall it felt more like a strong big tech data science process than some completely different AI-company thing, except they clearly assumed I was comfortable using AI tools and reading machine-generated code. Everyone asked some version of why OpenAI, so there was a slight missionary vibe, but safety and ethics mostly showed up later with PM and leadership. I made it all the way through and did not get the offer."