Im a 26 year old guy with an MBA and I work as an ERP system administrator. I have been interested in the field of data science for a while now. I've always liked statistics and various analytical tasks.

I would really like to try and work within this field, but it feels a bit overwhelming. People mention that you have to learn Python, R, SQL, Machine Learning, advanced algebra, data modeling, big data (hadoop etc), predictive analytics, various business intelligence tools, VBA, Matlab etc etc.

As of today, I have some SQL knowledge and have a general understanding of BI, big data, good excel skills etc. I am willing to learn some of the aforementioned areas, but I don't have the money or time to go back to full time university studies again.

So here is my question: is there any recognized "light version" of data scientist on the market? What are they usually called? What skills do they need to master? What should I learn in order to work with big data sets and analytics without having to study full time for another 5 years?

I live in Scandinavia so the job market is probably different here, but I thought it would be interesting to hear some answers.

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    $\begingroup$ I feel you got disappointed too soon. Start by taking data science MOOCs which are free and after getting a little bit into that, decide what to do. $\endgroup$
    – Hamideh
    Commented Mar 27, 2016 at 17:10
  • $\begingroup$ Ok thanks, how do you think employers view moocs though? Can you get a data science job by having just completed several moocs together with an mba? $\endgroup$
    – Ceylon
    Commented Mar 28, 2016 at 20:47
  • $\begingroup$ I don't even have an MBA, but I lead the data science and growth teams, and all of my education is through MOOCs (as included in my answer, my math education is through OCW) and online tutorials. So, unless and until you have the knowledge and skills to get the work done, the background don't matter in most cases. So, I definitely agree with @HamidehIraj's that MOOC's would defnintely help you get up and running. $\endgroup$
    – Dawny33
    Commented Mar 29, 2016 at 6:58
  • $\begingroup$ @Ceylon by taking MOOCs, I meant getting yourself exposed to data science topics for free and giving yourself time to decide. You can become a full data scientist but it seems that because of uncertainty, you are assuming that you can't. Start by MOOCs to get into that, you will find the optimal learning method for yourself then. $\endgroup$
    – Hamideh
    Commented Mar 30, 2016 at 3:21
  • $\begingroup$ A bit offtopic but may I ask where you live Dawny? Here in scandinavia its pretty difficult to get more sophisticated jobs without academic degrees, but I guess its becouse education is free and not very difficult to get. $\endgroup$
    – Ceylon
    Commented Mar 30, 2016 at 13:25

2 Answers 2


Business intelligence is perfect for you; you already have the business background. If you want to become a bona fide data scientist brush up on your computer science, linear algebra, and statistics. I consider these the bare essentials.

I don't know about Scandinavia, but in the U.S., data science covers a broad spectrum of tasks ranging from full-time software development to full-time data analysis, often with domain expertise required in various niches, such as experimental design. You have to decide where your strengths and interests lie to pick a position on this spectrum, and prepare accordingly. Useful activities include participating in Kaggle competitions, and contributing to open source data science libraries.


The business analyst flavour of data science is something you are nicely suited for.

As far as I have seen business analysts and business intelligence engineers in the industry, most of their work is centered around deriving insights from Excel sheets and writing SQL queries to dig out the appropriate data. They do write scripts, but that is generally for just the visualization purpose, and not for higher lever analytics like Machine Learning.

I can also see a nice future for you in the financial analytics/quant domain. It is also a domain where the learning curve is a bit steep, but totally worth it. Here is my answer on Quora about getting into the field of quant.

However, if you want to get up to speed with data science, then you have to slowly build up strong linear algebra skills, along with a very keen and valuable domain knowledge in whatever domain you'd be working with. The latter is often underrated, but from my (short but valuable) experience in the industry; I vouch for that fact.

Bonus resources:

  1. Quora data science topic wiki
  2. Metacademy learning paths
  3. OCW math courses

If you're okay with starting with a full blast ground up learning marathon for data science, then this is the path I'd recommend:

  1. Single Variable Calculus
  2. Multi Variable Calculus
  3. Differential Equations
  4. Linear Algebra
  5. Probability theory and combinatorics Basics
  6. Statistics
  7. Algorithms

All the above courses are available in the OCW catalogue. If not, then you can find them in other MOOC aggregators too.

  • $\begingroup$ Wow great, thanks! I've seen some business analyst job ads and it does seem like a more light version of data science indeed! Thank you for your answers to all my questions $\endgroup$
    – Ceylon
    Commented Mar 28, 2016 at 20:45

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