Career as Data Scientist
Data Science is an integrative subject which uses many statistical methods, scientific algorithms, information science, data analysis, machine learning concepts, and other related subjects to extract knowledge from a large group of data – both structured and unstructured to produce a strategy for the companies to know about their data and its analysis. Data Scientists possess industry-specific knowledge along with an ace in technical and programming skills. They write highly complex algorithms to bring large amounts of data together. Depending upon the output given by a data scientist, a company plans its business strategy and its plans. Data Science is an emerging career option in the present age. With a steep rise in big data, the biggest high tech companies to medium-sized firms have opened up positions for data scientists to make future predictions about the business based upon the data. The demand is going to increase in the coming future.
- About Data Scientist :
- Job Profile |
- How do I get there?
Job Profile
A work routine of a Data Scientist revolves
around data. They help the company make strong decisions and
improve business strategy in the competitive market depending upon
data analysis. They pull the data, merge it, and analyze the trends
in the data using many tools such as Python, MATLAB, R, Tableau,
Hadoop, SQL, and/or Excel. They write new algorithms based on the
analysis and tests them in real-time.
After the job is done, Data Scientist will conduct important
meetings with the clients and explain the data analysis and the
science behind it to the non-technical people of different
departments such as Sales, Marketing, and Planning, etc. The job of
a Data Scientist is an indoor-based one. The work pressure may
build up at times when the predictive models did not work as
expected or when the code goes wrong. The job of a data scientist
can be an individual as well as team-oriented work depending upon
the size of the company, nature of the business, etc. An average
work hour of a data scientist is up to 60 hours per week. There can
be extensions in the work duration depending upon the nature of the
business.
In an ever-growing industry of Data Science, the demand for employment is very high. This trend has been increasing in recent years. The most coveted roles in Data Science are Data Analyst, Business Analyst, Data Scientist, Business Analytics Manager, Data Engineer, Big Data Specialist and MIS Consultant/Data Visualization Consultant.
The average salary of an entry-level data scientist in India is around five to six lakh per annum. As the experience and skills increase, a person can expect from Rs 30 Lakh to Rs 50 Lakh per annum as the average salary. The salary can also depend upon the nature of the company you have been employed, the industry, etc. The different types of specialization in Data Science are Data Mining, Statistical Analysis, Cloud and Distributed Computing, Data Engineering, Business Intelligence, Data Visualization and Presentation, and Artificial Intelligence. These are some areas where people can get their expertise and be viable to the ever-changing needs of the industry.
Every role in Data Science offers the best
growth. No role in Data Science is stagnant. It is an icing on the
cake for the data scientist to enhance their knowledge and skills.
they will be in constant demand by the majority of the
companies.
|
Name of Job/Role |
Average salary offered (at 2-5 years work ex) |
Top recruiting companies |
|
Data Analyst/Business Analyst |
4 lakh PA |
Small and medium-sized companies |
|
Entry-level Data Scientist |
5 to 6 lakh PA |
Small and medium-sized companies |
|
Data Engineer |
8 Lakh PA |
BitCasa, Quora, Udemy, Shopkick, WePay etc |
|
Big Data and Hadoop Developer |
8.5 Lakh PA |
Microsoft, Amazon, Facebook, Google |
|
Big Data Manager |
16 Lakh PA |
Microsoft, Flipkart, Google |
|
Machine Learning Engineer |
7 Lakh PA |
Google, Apple, Facebook |
|
Senior Data Scientist |
17 Lakh PA |
MNCs |
Future Growth Prospects and How to get there faster
Pros and Cons of Being a Data Scientist
Pros
-
Highly rewarding career
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Abundant opportunities
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Unique and Challenging work nature
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Exposure to many industries and domains
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Job security
Cons
-
Ever-changing job prospects
-
Data Privacy is not ensured
-
Extensive Domain Knowledge required
-
A large amount of data cannot be manageable every time
How do I get there?
Any student who intends to seek a career path in
data science after
10th
-
Can opt for science stream in higher secondary.
-
Concentrate on learning PYTHON programming language along with Statistics and MySQL.
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Develop an interest in Artificial Intelligence (AI), Machine Learning (ML).
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Keep track of recent developments in AI and ML. Follow the companies depending upon AI on Social media.
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Expose yourself to the world of AI. Keep writing the sample code.
Any student who wants to make a career in data science after
12th
-
Many colleges are providing a Bachelor’s degree in Data Science and Analytics. Students can opt to study it or can take a degree with computer science as the main subject.
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Strong statistical and mathematical skills will help you shine in the data science field. Practice them thoroughly.
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Degree in Statistics or Mathematics can also help you along with programming skills.
Students who complete graduation and want to
take up data science as their career
-
Can choose masters science and analytics.
-
Can choose a master’s degree in Mathematics/Statistics along with an online course in Python for Data Science or an online course in Hadoop or Big data.
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Join the community of Data Scientists in Social media and be up to date with all the recent developments in the industry.
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Know R Programming, its uses in data science. Study about managing Big Data with R Programming.
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Learn about Data Visualization tools such as Tableau, Kibana, Qlikview, etc.
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Go for some sample data science projects from Kaggle.com to get hands-on experience.
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Take up online certifications in Data Science from Udemy, Udacity, Simplilearn.
Students who complete Post graduation can go for PhD programmes in Data Science along with the courses mentioned above to be done after graduation. Students should be aware of the developments in the Data Science field and never stop learning even after their education is complete. To get promoted to the next level in this field, one should keep track of every small change in Data Science and its related fields.
How much does it cost ?
What are the Top Colleges where one should be studying to become a Data Scientist?
Data Science is an ever-evolving subject and
gaining popularity from the past three to four years. Below are
some of the premier colleges in India which offer Data Science
courses.
|
Rank of College as per 2019 |
Name of College, City |
Programme Fees |
|
1 |
IIT Kharagpur, IIM Calcutta and ISI Kolkata |
PG Diploma in Business Analytics – 2 years – Rs 20,00,000 |
|
2 |
Jigsaw Academy by MAHE (Manipal Academy of Higher Education) – Bengaluru and Hyderabad |
PG Diploma in Data Science – 11 months – Rs 4,95,000, |
|
3 |
Praxis Business School - Bengaluru, Kolkata, Tirupati |
Post Graduate Program in Data Science - 9 months – Rs 5.4 Lakh. |
|
4 |
Great Learning – Bengaluru, Mumbai, Chennai, Gurgaon, Hyderabad, Pune, and Online Classes |
PG program in Artificial Intelligence – 5 months - Rs 2.4 Lakh PA to Rs 3.6 Lakh PA |
|
5 |
NMIMS’s Mukesh Patel School of Technology Management & Engineering - Mumbai |
M. Tech Data Science & Artificial Intelligence – 2 years - Rs 5 Lakh PA. |
|
6 |
International Institute of Digital Technologies - Tirupati |
PG program Business Analytics – 1 year- Rs 5 Lakh. |
|
7 |
Symbiosis Centre for Information Technology - Pune |
MBA Data Sciences and Data Analytics – 2 years - 13.14 Lakh PA. |
|
8 |
S P Jain School of Global Management |
Graduate Certificate in Big Data and Visual Analytics – 8 months - Rs 5 Lakh. |
Books and other Study Material
Some books which can be of great help to students who wish to take up a career in data science are:
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Python Data Science Handbook by Jake VanderPlas
-
Think Python by Allen B. Downey
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Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David
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Practical Statistics for Data Scientists by Peter Bruce and Andrew Bruce
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Python Machine Learning By Example: The easiest way to get into Machine Learning
-
Python for Data Analysis by Wes McKinney
What if this career does not work out for me? What are the other options for a person with these credentials?
Other careers of your interests
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Content on this page is by Career Expert Mrs. Kum Kum Tandon MA (Psychology), M.Ed, Diploma in Educational Psychology, Vocational Guidance & Counseling (NCERT, Delhi) | View Complete Profile |