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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.

Ethan
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Ceylon
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2 Answers2

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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.

Emre
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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.

Dawny33
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