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Chief
Hello fishes,
Need help.
YOE: 10.5, java
Offers in hand:
Evoke technologies - 28lpa
CDK global - 30 lpa
Ness technologies -30 lpa
All are fixed components.
Which one to choose?
I prefer to have WLB, job security, decent hikes to stay long term in the company.
Cognizant Tata Consultancy Evoke Technologies Ness Digital Engineering CDK Global Inc Infosys
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As a PhD, go for Senior consultant. Salary depends on the location, team etc.
Do you want to continue to do any truly complicated analysis or anything that comes close to data science? If so I then look for data science roles, consulting firms all vastly oversell how much complex analysis they do.
Rising Star
As a PhD in data science, why consulting?
If you want to lean in to the data science side you should go for BCG Gamma, McKinsey QuantumBlack, Deloitte Analytics and Cognitive, Accenture Applied Intelligence.
GAMMA has DS roles aligned to optimization and roles for ML models. I think you could go for either.
OP - have you considered BCG gamma, or DS jobs at banks (eg Capital One)?
For Data Science consulting, Accenture’s Applied Intelligence or Deloitte are your best options. Accenture has a bigger footprint and overall having been on the client side is the one that can take you from 0 to 100 with resources and tools very well established, Deloitte is a bit behind but no too behind, Accenture does pay more per the public salaries and chatting with a few people between both. McKinsey, BCG or Bain may be prestigious, but not really in Data Science, going there for Data Science you will be doing work for 2-3 people, it really isn’t their thing, as a data scientist you will be frustrated and ridiculously overworked. Hope this helps. Let me know if you need more insight.
McKinsey and BCG have spent hundreds of millions (if not billions) of dollars in investment to acquire and develop digital talent of all kinds. I wouldn’t mention Bain in the same sentence to someone thinking of DS consulting because it’s not just about prestige - it is about capability and seriousness when it comes to playing in this space.
I can’t speak for how McKinsey does things, but I am a DS at BCG Gamma. If by “doing work for 2-3 people” you mean there are very few people who sell DS work, I’ll just say that we have about a thousand consulting-track data scientists and AI Software Engineers at this point, mostly in Europe (France and Germany) and North America. We have data science projects in every industry across topics like optimization, prediction, content recommendation, and deep learning (although that tends to be more rare and niche). Top Gamma MDPs are booking as much revenue as almost anyone else at the firm, and more and more cases are incorporating DS capabilities because the clients, partners, and staff believe this is a big part of the future of BCG.
I am not going to deny that Accenture AI is a market leader in this space. They have a great reputation and do very fine work. But here I will bring up an MBB selling point: we work with company leadership. At BCG, the cases I’m on are not just providing one off solutions within an existing framework, but often we are laying out the entire analytics strategy for a company, how they should build their own DS capabilities, how to set up and hire that department. This kind of exposure to senior decision-making environments is tremendous for growing as a professional.
Another thing I can’t deny is that you may in fact be frustrated and overworked. But no more, on average, than the generalists working alongside you. BCG can be a grind depending on who you work for and what case you’re on, regardless of whether you are a generalist or DS. But just as we share the tough WLB, DSs also share the same career progression levels, salaries, and path to partnership as any other consultant at BCG (except at the junior level where we’re paid more. In some ways we even have more options: less up-or-out, option to work for a startup for up to 3 years and still get 50% promotion tenure, less risk of being pigeonholed into a particular industry, etc.
Right now we have too many cases that want DS and not enough DS to go around. That can mean less downtime between cases. But it also means the firm will work to accommodate your limits so you don’t burn out and worsen the shortage. If you find a good team and set boundaries, I dare say you can even achieve significantly better WLB than the average generalist.
And if that still doesn’t work out, you can exit to FAANG and similar tier companies. That’s where a lot of the people who leave, leave to.