What it takes to land the “Sexiest Job of 21st Century”
According to Harvard Business Review, Data scientist might be the sexiest job of the 21st century, but it’s hardly an easy gig to land. As not many people are really sure how to go about preparing themselves to become a data scientist. So what exactly do you need to know in order to land this hot job?
Who is a Data Scientist?
Anjul Bhambhri, Vice President of Big Data Products at IBM, says, “A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization.” A data scientist has a very valuable role to play in today’s economic scenario. With multiple sources of data bringing in information to the business, the data scientist must use his skills to find the relevant insight. The relevancy may be that it is a competitive advantage or a business solution. A data scientist must continuously question the existing patterns and theories. An experimental and inquisitive mind is required to ‘mine the data’ and find the information that is to be conveyed to the leaders of the organisation.
How to become a data scientist?
Becoming a data scientist is a hard task. It requires great commitment to the field and extensive hard work. There are certain skills that one may look for in a data scientist. So, what exactly are these skills?
- Coding: At the most basic level, data scientists are expected to know how to code in Java, SCALA and C++. Talking about more advanced coding, Python and R are the most used languages for a data scientist.
- Mathematics and Statistics: A data scientist is expected to be at ease with mathematics and statistics. Under mathematics, linear algebra, calculus and probability/ Combinatorics are the tools used. It’s very common for Data scientists to analyse data using Distribution, Summary Statistics, Hypothesis Testing and Bayesian Analysis.
- Machine Learning: Machine learning is an integral part of data science. It holds a superior place in a data scientist’s arsenal. Both supervised and unsupervised machine learning are important for a data scientist. A data scientist should be comfortable using SVM, Random Forest, K-means, LDA, Information Retrieval and Model Comparison.
- Software Engineering: Data scientists have to often use Data Visualization and Data Munging. For this they need to be very familiar with software engineering concepts such as Algorithms and Data structures.
What are employers looking for?
When the employers are looking for data scientists, there are a number of qualities that they search for. They want a data scientist to be a data hacker, an analyst, an adviser whom they can trust and most importantly, a communicator. These qualities are very important as the employer’s base a number of important business decisions on the advice of the data scientists. A lot of companies are hiring by the numbers, and they are still in need for more data scientists. It is of no surprise that the average salary ranges around $ 115,000 a year! A gold mine waiting to be explored, if you ask me!
Check out these hot Data scientist jobs–
Delhivery – Data Scientist – Machine Learning (4-10 yrs)
Hadoop Developer – IIT/REC/BITS (3-15 yrs)
Data Integration Expert (7-12 yrs)