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A History of Data Science
The much discussed title “Data Scientist” has been as problematic as it has exciting for many people within the Analytics space. “Data Science” has emerged only recently to specifically designate a new area that is expected to make sense of the vast stores of big (unstructured or otherwise) data that we produce as a society.
If you follow our consultant @NiallWharton you will have seen his appreciation for those who are helping to set the field within a continuous context and produce recognised definitions for this relatively green area. One excellent contributor to the discussion is Gil Press; his two recent contributions to Forbes about the history of Data Science and Big Data have been widely acclaimed.
What is a Data Scientist?
Hortonworks’ Ofer Mendelevitch describes the ideal Data Scientist as occupying a place on the spectrum between a software engineer and a research scientist;
Software Engineer – Data Engineer – Data Scientist – Research Scientist – Statistician.
This will vary from company to company.
What Skills Do I Need to be a Data Scientist?
A blend of programming and statistical analysis skills will make up the foundations of your career as a Data Scientist.
Traditional analytical tools such as SQL, SAS, and SPSS are now the basic requirements that one might possess to build with familiarity in R, Hive, Pig and the Hadoop Ecosystem in general. The tool has unavoidably risen to the fore in Data Science but real value lies in building on the platform to get more specific insight. In terms of programming, companies will often prefer you to be as language agnostic as possible, but knowledge of Python in particular will go a long way.
The focus placed on creating and implementing the appropriate algorithms within companies has led to an appreciation of those candidates with backgrounds in;
Remember, to gain a job within the largest companies in the world there must be evidence of using this within a business environment for real world solutions.
There is no doubt however that the minimum requirements for such roles will include an MSc/PhD in a Computer/Numerate related area.
Graduate Data Scientists and Transitional Data Science Professionals
So having gained an idea of the skills you need, how can you attain them from here? Although there is a lack of specific academic studies, there are some useful courses in some of Britain’s top universities, take a look at some here;
But for those who cannot take the time to study on a full time course (as well as those who can), there are some excellent online methods of study that can improve your experience and knowledge.
The first example is Coursera’s fantastic (and free!) remote Data Science/ Machine Learning courses. These are widely recognised as the first step to gaining a practical working knowledge.
Once you have completed the course and want to test your skills against the best in the business, Kaggle’s testing online Data Science competitions are another form of universally recognised experience. http://www.kaggle.com/competitions
Finally, we recommend meeting up with fellow professionals to gain more insight from experienced Data Scientists. The London Data Science Meet-Up groups are thriving and have rapidly grown in popularity – book your places quickly!
It is important to note that for all the skills that one may develop through courses or experience, the most important attribute to possess as a Data Scientist is a naturally inquisitive and intelligent mind.
How Do I Get a Job From Here?
There has been a sharp rise in the amount of Data Science departments throughout the UK that ultimately answer to themselves, rather than being tagged on to Business Intelligence or general Analytics teams. In this way, we now deal with far more Chief/Senior/Graduate Data Scientist roles than ever.
We recruit for positions in a huge number of sectors including healthcare, e-commerce, and publishing and these are with some of the largest companies in the world.
If you are in need of a new challenge (or know someone who is), and would like to learn more about some of our current opportunities in Data Science or our clients, please contact Niall on 0203 301 9908 or email@example.com. Also make sure to search all of our current vacancies.