The keys to becoming a data scientist: Exploring modern career frontiers

Data Science   |   
Published December 29, 2015   |   

If you know someone who is obsessed with data or if that is something that interests you and you are looking for a smart career move, there are opportunities right now to become a data scientist.
It is now easier than ever before to complete something like a sas training course online for example and get your resume up to speed so that you are ready to take on a new direction in your career, including the feasible option of fulfilling a growing need for data scientists.

What does a data scientist do?

A data scientist is someone who is tasked with pulling together statistics, computer science and data analysis into a manageable format.
This data that is collected and can then be mined and utilised for creating strategies that can be useful for growing a business and finding new customers.
The reason that a data scientist’s skills are in such demand is that being able to collect raw data and analyze it such a way that it can then be used to generate valuable insights and identify trends, is something of value in a digital marketplace.

A range of skills required

It is not just the right technical skills that you need to become a data scientist, you will also need to display and possess some non-technical skills and attributes which will serve you well and allow you to carve out a career.
Every company that is looking for data scientists will almost certainly take a slightly different slant on the skills you need and maybe require a stronger emphasis on some abilities and knowledge than others.

Technical skills

An analytical brain is a needed to be a successful data scientist and many of the people who are already earning a living in this industry are also highly educated.
The majority of data scientists have a Master’s degree and about half have a PhD to their name. If you have a mathematical or scientific background already and maybe some knowledge of statistical analysis, you will already have the usual technical skills needed to kick-start your career in this field.
If you already have an in-depth knowledge of SAS or an equivalent analytical tool, this will be an asset, and you can prepare for your career as a data scientist by acquiring these additional qualifications if needed, by studying whilst continuing with your existing work.

Computer science

Some of the other recognized technical skills considered as necessary if you want to be a data scientist, include a working knowledge of Python coding, Hadoop Platform and ability to work with SQL database coding.
Another critical requirement would be an aptitude for working with unstructured data from various channels and platforms such as social media and video feeds.

Non-technical skills also needed

There are a number of soft skills that would be a great asset in your quest to become a data scientist as outlined by recruitment specialists in this field and these include an element of intellectual curiosity and a good business acumen combined with strong communication skills.
A data scientist is often expected to arm the business with the information that will allow it to make decisions based on your quantified insights. This is where the strong communication skills will prove an invaluable asset as you will have to be able translate your technical findings to what is often a non-technical team, who will be wanting to use the data.

Learn to code

If you are keen to explore the possibility of becoming a data scientist, one of the fundamental requirements will be an ability to work with and understand coding.
If you don’t already have this skillset, you can always learn to code and as the things that you eventually build will need to be integrated into other systems, you will need to get a good grasp of end-to-end development.

Learn about data munging

If you are not familiar with what data munging or data wrangling involves, it is the process of converting or mapping raw data into an alternative format so that it can be interpreted and utilised more easily.
Part of this overall process will also include data visualization, which involves the creation as well as the study of the visual representation of the data. You will also be expected to put this data into a comprehensible report so that anyone who does not have the same technical skills as you, can easily read and understand the data being presented.
Make no mistake, becoming a data scientist is definitely no walk in the park, but the rewards in terms of salary and job satisfaction, are there for all to see.