STEM Career Spotlight: Data Science and Data Analytics
The best part about STEM education is that there is no dearth of jobs in the market. Here, we are specifically going to talk about the field of data science, which is the next big thing.
What are data science and data analytics?
Before going any further, let’s first understand the difference between data science and data analytics. Data science is a broader term that comprises of approach to handling big data. It involves preparation, analysis and cleansing of data. As a data scientist, a professional has to collect data from multiple resources and use techniques like predictive analytics, machine learning, and sentiment analysis to derive information that’s applicable in a particular process.
Data analysis, on the other hand, involves descriptive statistics, data visualization, and data communications for meaningful conclusions.
The current scenario of data science jobs in India
The Edvancer & Analytics India Magazine presented stats related to jobs in analytics and data science this year (2018) and the results were intriguing. The study reported around 76 per cent rise in the number of analytics jobs a month in April 2018 when compared with April 2017. The interesting part is that the 98 per cent of jobs in this sector are full time.
Talking about the city-wise requirements in the sector, Bengaluru topped the chart with 27 per cent of jobs in India, followed by Delhi with 21 per cent jobs.
Demand in different sectors
Let’s now put our focus on different sectors where data scientists are needed. The highest demand is from the finance and banking sector. In fact, around 41 per cent of jobs are from these industries. Other industries where data science professionals can make it big include energy & utilities, healthcare, online retail, entertainment, telecom, and automobile. It is expected that other sectors, like hospitality, education, travel, and retail, will also start to rely more on data analysis professionals after realizing their professionals.
Skills needed to become a data analyst
What differentiates a data analyst from other professionals is that the individual needs to be proficient in multiple skills. A data analysis enthusiast must be fluent in programming languages like Python; should understand PIG & Hive (popular tools for data analysis) and must have adeptness related to statistical methods.
What else should an enthusiast do?
Apart from honing the above-discussed skills, a data science/analysis enthusiast must follow data science professionals and academicians that have already made it big in the world. Some popular academicians from India include:
- Arun Reddy from UpX Academy
- Bappaditya Mukhopadyay from Great Lakes Institute of Management
- Chandrasekhar Ramanathan, IIIT-B professor
- Dinesh Kumar from IIM Bangalore
One can also begin by going through the books specifically written for the beginners. Some of these books include I heart logs by Jay Kreps, Lean Analytics by Croll & Yoskovitz, Naked Statistics by Charles Wheelan, and Doing Data Science by Schutt and O’Neil.
Salary as a data scientist
The average salary in this profession is Rs. 620,244 per year, as per the website PayScale. If you acquire sufficient experience (more than 10 years) and become proficient in this field, you can become Chief Data Scientist and touch the mark Rs. one crore.
The skill gap
As discussed above, data analysis and data science is an amalgamation of multiple abilities. Due to lack of data scientists and analysts, the programmers are hired to perform these roles. As they lack skills like data wrangling or the use of statistics efficiently, they fail to deliver the results expected from them.
How does STEM learning at early stages help?
If a student starts acquiring programming skills at an early age, they will not get intimidated by the complex nature of the job. The languages like Python, which are inevitable for data science roles, are taught through educational kits and robotics, thereby making them easier to understand and apply.
As the STEM approach integrates mathematics as one of the core areas of learning, statistical methods also look like a piece of cake as the students apply them in their respective jobs.
That’s just not it. Problem-solving and critical thinking skills lie at the core of the STEM education. And one can’t expect to thrive in the job of data science and analytics if he/she lacks these skills. This is why it’s a good decision to enrol the kids in a course that involves STEM-based learning. You can also check with your child’s school on whether they have similar provisions in the curriculum.
And when the students finish their schooling, they must look for courses that specifically revolve around data sciences and analytics.
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