MBB Consulting vs. Data Scientist (and vs. Deloitte)
I am a data scientist who wants to work on strategic-level issues for an organization (doesn't everyone... haha). I just finished an MS from a top tech school (Berkeley/MIT/Carnegie Mellon/Stanford). Having technical work is very important to me, but what's more important to me is to have an established career at the corporate level. So with this in mind, I am hoping to decide between several opportunities. Which should I pick? Or, is my understanding of the pros/cons accurate? I don't intend to stay at any of these for more than 2 years.
1. Deloitte analytics consulting; consultant-level
- Pros: (Maybe?)Strategic-level impact. I'd be a young consultant--I'm 22--which might be impressive for exit ops. Might get a middle-management exit op earlier than I'd get if I started as an entry-level data scientist. Good place to exercise my speaking/presentation skills. Supposedly very meritocratic promotions.
- Cons: Less technically capable than tech companies. Not where I want to be long-term. Supposedly Deloitte does a lot of due diligence/implementation, not strategic-level projects. Limited opportunity for depth. Unsure if it'd accelerate my career.
2. Data scientist position established tech company (e.g., think Microsoft, Amazon, etc.); entry-level
- Pros: Good pedigree for a scientist. Rotational program. Very technically hard problem sets. Hope that I picked the "right" side as industries change to be more data-centric.
- Cons: I'd be a busy-bee at the entry-level--no strategic-level work initially. I might get stuck at the low, with limited promotion ops.
3. McKinsey (interview stage, so not likely, but I need to think about this); unsure
- Pros: Better than Deloitte in terms of prestige, exit ops, strategic impact.
- Cons: Mostly non-technical. Less technically capable than tech companies. Exit ops might be too high-level because I don't develop any depth. Supposedly a lot of ex-MBBers do "corporate strategy" where they just write white papers with zero influence. Negative stereotype they're just expensive people that tell you what you already know.
McKinsey and the other MBB firms also have Analytics Consulting.
I was in your shoes this past year. Essentially what you've layed out here is that there's a spectrum in this new data age for data science careers. Business on one side, and pure data science on the other. McKinsey generalist falling more on the business side, Tech more on the pure DS side, and Deloitte somewhere in the middle.
Without thinking about these companies specifically, you need to figure out where you want your career to fall on the spectrum, though you don't necessarily need to decide now. There are a lot of pros and cons to each place - it really depends on what your values are and what you enjoy doing in the realm of data science. I.e. do you enjoy doing the difficult technical work or working on the bigger picture. It sounds like you're somewhere in the middle, but lean a bit more to the pure DS side. You can always move on the spectrum later in your career, but I will say I think it's easier to move from DS to business on the spectrum than the other way around.
Now speaking about companies specifically, I know very little about Deloitte but can speak about the other two options a bit. I would dispute your point about not developing depth at MBB. Even as a generalist you can build a focus in both industry and function if that's what you want to do. There's a lot of flexibility at McKinsey - if you don't like being a generalist you can shift to a more technical analytics track, or focus on industries that you like over others. McKinsey also hires many Data Science PhD expert level people - and within that, there is a spectrum of people who consult vs people who are more technical resources, so I don't think the caliber of DS is necessarily significantly worse at McKinsey than elsewhere. Exit opps are certainly not limited to "corp dev" and I've seen tons of ex-McKinsey consultants develop passion on certain topics and join opps in those fields.
For large tech, I mostly agree with your analysis - at some point it's going to be hard to progress past a certain point without business-side exposure. But you always have the MBA option. The one thing I would add is that the type of problem you work on here is probably not going to be at a high strategic level. A FB Data scientist is going to be analyzing how a new ad impacts site traffic, while a consultant will be working on problems that affect the company as a whole.
Feel free to PM and I might be able to give you more details about my experience