Data Science & Data Scientist
With the advancement in technology, we happen to see new roles emerge. As more advancements are coming and with the passage of time, we happen to have more data to manage, analyze and make most use out of it. Hence the role ‘data scientist’ has emerged. The data scientist role has been nominated as the best role for 2016 in US (https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm )
The name itself provides some insight of what this role is about. Science is about studying something in a systematic way, data is used to produce information and knowledge. Hence the role is about studying data in a systematic way, hence producing valuable information to be used by the concerned organization.
As this role is still in its infancy to draw a boundary what is exactly expected out of this role. We may say this role revolves around extracting knowledge from the ocean of data. The digital footprint is expanding exponentially. Each and every act we do creates a bunch of data, which can be used for sales, marketing, analysis, prediction just to name a few. By utilizing the skills, data modelling and statistical analysis, data scientist should now only analyze the old data but to predict future plans and patterns on its basis.
Some of the skills data scientist should have are but not limited to:
- Analyzing data with mathematical approach. This will involve utilizing skills like data mining, statistics and/or machine learning.
- Have a strong computer science background with the inclination towards algorithm and working knowledge of API’s like Hadoop.
- It would be best to have statistical knowledge and knowing a tool which applies statistical principals would be great along with the database languages like SQL.
In an organization that support evolution, this could rather be a very good experience. The data scientist could be working with analyzing data using techniques like Excel pivot tables or some other third party tools. Or to look at google analytics to take out some hidden information for strategists. Nevertheless data scientist position is challenging, joyful & ever evolving.
Briefly, the data scientist has to perform these activities very frequently:
- Data Analysis
- Data Warehousing
- Data Visualization
- Data Wrangling or Data Munging or Data Mapping: In a nutshell to work on missing data, using the domain knowledge & expertise as data scientist
- Machine Learning
All in all, this is an exciting area working with Big Data using all the techniques learned in Mathematics, Statistics, Software Engineering, Tools expertise & Domain Knowledge, the best part is to be called a ‘Data Scientist’.