3/1 Langs Road, Ascot Vale, 3032 Victoria, Melbourne, Australia
+ 61 4 3538 1719
Home»Data Science»Data Science is not just for those with PhD’s

Data Science is not just for those with PhD’s

It is a common misconception that data science is a field only for PhD’s. Field of data science is a vast and welcoming playground for anyone with an aptitude for problem solving using data.

Data Science is the intersection of three key areas:


  • Domain knowledge
  • Computer programming
  • Math and statistics

Domain knowledge is just the knowledge of the industry or field one is working in. A financial analyst would have knowledge about the stock market. A hotel manager would have knowledge about the hospitality industry. A sales manager would have knowledge about what factors influence buying.


Computer programming is the ability to use code to solve various types of problems. Many of today’s programming languages have a syntax closely resembling general English. Picking up programming is not as difficult as it used to be.


Math and statistics is the use of equations and formulas to perform analysis. Many of these concepts are from school or college days. Of course one can dive deep into the various theorems and derivations. But many of today’s freely available tools handle these complexities behind the screen.


In order to gain knowledge from data, one must be able to utilize computer programming to access the data, understand the mathematics behind the models we derive, and above all, understand our analyses’ place in the domain we are in.


When starting off in the field of data science, one would rely on their core strengths depending on which area they come from. Someone with a background in programming would be exploring the application of code to derive mathematical models. Someone with a background in math would be trying out coding. Someone with domain knowledge would be creating hypotheses to test using code.


The intersection of math and programming leads to what is referred to as machine learning. However, one needs to be able to explicitly generalize models to a domain so that a business problem can be addressed. Any business problem can be represented as a mathematical equation. Math and coding are vehicles that allow data scientists to step back and apply their skills virtually anywhere

Written by

Prakash Roshan is a Data Scientist and the founder/creator of iKompass, iNurtura, ITPacs. Roshan is a technology entrepreneur passionate about coding. Roshan has authored various books and articles on data science, programming and project management. His core interests lie in bringing statistics, technology and human behavior together. Roshan has led and managed projects for many MNCs in a consulting role. His most recent stint has been with a major investment bank to use machine learning to identify malicious behavior. Roshan likes solving complex problems through creative solutions. Most of his career has been around finding creative solutions by merging data, technology and human motivations. This stems from his college background in Statistics, computer science and psychology. Roshan has a masters degree from the University of Birmingham. When he is not coding or refining algorithms, he is busy doing muy thai, Scuba diving, rock climbing, tennis or hiking. Roshan is a very big fan of the authors Daniel Kahnman and Amor Tversky. He spends time in Singapore, New York and London each year.