CMU Tepper vs UC Berkeley Econ (+ DS or Stats) for technical finance roles

Hi! I’m an incoming freshman deciding between CMU (Tepper Business school interested in Computational Finance) and UC Berkeley (Economics in L&S, planning to add Data Science or Statistics), and I’d really appreciate any advice.

I’m especially interested in more technical and quantitative heavy finance roles (applying math, stats, and some ML to markets — but not really quant dev or heavy SWE).

Here are the main factors I’m trying to weigh:

1. Academics / Preparation for Finance

CMU: Tepper + potential Computational Finance major seems very targeted and quantitative

Berkeley: Econ + DS/Stats seems flexible, but I’m not sure if it’s as structured for finance.

2. Access to Opportunities (clubs, research, recruiting)

I’ve heard Berkeley clubs can be very competitive — how hard is it to actually get involved?

At CMU, does being in Tepper make it easier to access finance-related opportunities?

3. Career Outcomes (NYC / Chicago vs SF)

I want to work in NYC or Chicago, ideally in trading or hedge fund-type roles

Does Berkeley tend to place more into SF/West Coast?

How strong is CMU/Tepper placement into finance roles outside Pittsburgh?

4. Double Major / Flexibility

How manageable is adding Stats/Data Science at Berkeley?

At CMU, how easy is it to double major or add something more quantitative alongside Tepper?

If anyone has experience with either, I’d really appreciate your perspective. Thanks so much!