7 Key Skills of Effective Data Scientists


Are you looking for an exciting career opportunity that is just as paying as it is desirable? Harvard Business Review calls Data Scientists are the sexiest jobs of the 21st century. Data Scientist term coined when two people, DJ Patil and Jeff Hammerbacher, were trying to name their data team working on big data and did not want to limit their functions with just any job title like business analyst or research scientist. And ever since, the title has become extremely popular. Data scientists are someone who is inquisitive and who can stare at data and spot trends. Individuals in this particular role don’t just sift through and organize piles of information for companies; they are part of a cross-functional team within an organization who provide various departments with pertinent information to facilitate growth and innovation. Now that you know what a data scientist is, let’s discuss how you can be on your way to be an effective Data Scientist. 


1.    Diverse Technologies – a good Data Scientist is handy with a collection of open-source tools — Hadoop, Java, Python, among others. Knowing when to use those tools, and how to code, are prerequisites. To be a Data Scientist, you should have your hands on a number of tools and technologies, especially open source ones, such as Hadoop, Java, Python, C++, ECL, etc. Besides, having good understanding of database technologies, such as NoSQL database like HBase, CouchDB, etc. is an add-on.


2.    Mathematics – The second skill, as you might expect, is a base in statistics, algorithms, machine learning, and mathematics. Conventional computer science degrees no longer satisfy the quest of a data scientist. The job requires someone who on the one hand understands large-scale machine learning algorithms and programming and on the other is a statistician. So, the profile is better suited for experts in other scientific and mathematical disciplines, apart from computer science.


3.    Business Skills – As data scientists wear multiple hats, they need to have strong business skills. A data scientist has to communicate with diverse people in an organization that includes communicating and understanding business requirements, application requirements and interpret the patterns and relationships mined from data to people in marketing group, product development teams, and corporate executives. And all this requires good business skills, to get the things done right. 


4.    Visualization – The fourth set of skills focus on making products real and making data available to users. In other words, this one’s a combination of coding skills, an ability to see where data can add value, and collaborating with teams to make these products a reality. You may be able to mine and model data, but are you able to visualize it? Well if not, mind that you should be able to work with some, at least a few of the data visualization tools. Some of these include Tableau, Flare, D3.js, Processing, Google Visualization API, and Raphael.js.


5.    Innovation – You don’t just have to look around and do with data. You got to think creative, and innovate. A data scientist should be eager to learn more, be curious to find new things, and think out of the box. They should be focused on making products real and making perfectly done data available to users. They should be able to see where data can add value, and how it can brings better results.


6.    Problem-Solving Skills This may seem obvious, of course, because data science is all about solving problems. But a good data scientist must take the time to learn what problem needs to be solved, how the solution will deliver value, and how it'll be used and by whom.


7.    Communications Skills – Communication is the key to work with various cross-functional team members and present analytics in a compelling and effective manner to the leadership and customers. In other words, you may be brilliant in your rarefied field, but you're not going to be a really good data scientist if you can't communicate with the common folk.


Everywhere around us, data are being collected at unprecedented speed and scale — from online social networks and ecommerce sites to sensors in laboratories and smart utility meters. In order to unlock the powerful potential of this big data ------------the world needs Data Scientists and if you have the above mentioned 7 skill sets, you are all set for the exciting journey.

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Comment by rajesh mohan on August 29, 2015 at 7:47am

Should be a great story teller.  Ability to convert the results of analysis into a story is a wonderful skill to have.

Comment by Raj Verma on May 30, 2014 at 4:40am

The list is pretty impressive. Thanks Ms. Ghosh.

For Data Visualization I would add the dimensional charting library dc.js. dc.js is built on d3.js and crossfilter.js. and supports efficient exploration of large multi-dimensional datasets.

Comment by Vasilis Hatzopoulos on May 9, 2014 at 11:41pm

A sort of meta-skill of all the above is high mental bandwidth and multi-scale thinking. You need to be able to engage with and read/write various and sometimes wildly differing sources of information. Programming, mathematics, communication, aesthetics, business, marketing, web thechnologies,  etc span a very large range of grammars, modes of operation and codes of conduct

Comment by Vasilis Hatzopoulos on May 9, 2014 at 11:14pm

Also ggplot (R) for visualization is a must. I found that learning it helped/forced me to think deeper about the stories I want to tell as an analysis endpoint and mentually visualize the 'data geometry'

Comment by Sumedha Sengupta on May 5, 2014 at 2:11pm
The list provided above by Ms. Ghosh is quite impressive but a Data Scientist with all that desirable prerequisites might be hard to come by. Having worked as an applied statistician, I tend to agree on a team work approach. This way, experts in each discipline can interact and optimize the resources, utilize efficiently without too many duplications or replications of steps. Each may be an expert but may not be a ' Perfect' Data Scientist. At the level of expertise, each will have the desirable comprehension and communication skills. I believe it is possible and actually we see that more common than one person controlling the whole data stream from input to output and fulfilling all those desirable qualifications.
Comment by Matt Oates on April 6, 2014 at 1:35pm

The department that I work for ditched the typical IT name and we are now branded as "Technology Innovation" which I thought was pretty cool.

Comment by Randy Bartlett on March 24, 2014 at 12:44pm

I like the emphasis on innovation.

Comment by MuraliKrishnan on March 21, 2014 at 5:48am

Good and Thanks for the list.

Comment by Mousumi Ghosh on March 18, 2014 at 4:27am

The Business Skills section addresses that.

Comment by Vincent Granville on March 18, 2014 at 4:25am

I would add domain expertise.

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