We discuss how to become a data scientist Data scientists are analytical experts who utilise their skills in both Technology and Science to seek rent and manage data. They use industry knowledge, contextual understanding, scepticism of existing assumptions to uncover solutions to business challenges. Data scientists are the ones who manage and handle data. They are very much in demand as they know how to control and change the biggest and largest thing in this world.
Why should you learn data science?
Data science is one of the most attractive jobs in the present data driven world. More and more organisations ranging from small scale 2 large Enterprises have realised the importance of data science and implemented its capabilities to successfully scale up their business to new Heights.
- Demand vs supply
- Data science and analytics will create 11.5 million jobs by 2026.
- India is the second most prominent data science hub after the USA.
- there is a lack of skilled data-literate professionals in the market.
- increased demand by 29% in consecutive years and at 344% increase since 2013.
- Lucrative salary
- Harvard Business Review has referred to data scientist as the sexiest job of the 21st century.
- The average pay scale of a data scientist is way above other it and management sectors.
- Average salary per annum- $150,000.
- The technology of the future
- Data science is the technology of the future. New Tools and techniques keep emerging every day.
- Brilliance of bytes of data get generated daily. Therefore, data science will play a crucial role in the progress of various industries.
- Data science along with Quantum computing has a great scope in the future.
- provides insights from Complex metadata to make business decisions.
- There are several job options available ranging from Business Analyst to machine learning engineer.
- A data scientist can work in any part of the world.
- Data science is not only a technical field, rather it is more of a creative field.
How is the data scientist domain so lucrative?
- An entry level data scientist with less than one year of experience can earn rupees 50000 per annum.
- Early level data scientists with 1 to 4 years’ experience get around 610811 rupees per annum.
- Data scientist with 5 to 9 years experience on rupees 1,004,082 per annum in India.
- Senior level data scientist around more than rupees 1,700,000 per annum.
What are the skills required?
- Programming skills– statistical programming languages like python or R and a database query language like SQL.
- Statistics- which statistical test distributions maximum likelihood estimators etc.
- Machine Learning- how the algorithms work.
- multivariable Calculus and linear algebra- familiar with fundamental Engineering Mathematics.
- Data wrangling- how to deal with imperfections in data.
- Data intuition- a data driven problem solver.
How to attain those skills?
- Start with online study- online courses related to data scientists.
- Mugging up the data- read as much as you can on data science that includes academic paper textbooks, current industry reports, blogs on data and Tech based articles.
- Try to socialize in the DS community- Let yourself be involved in the data science community and learn more from your peers.
- Mentorship guidance- find a mentor at various sites available on Google to pose questions and hear their experiences.
- Focus on learning rather than creating- initially stick to Script free processes that are automated tasks and lean heavily on framework and databases.
- Start contributing to open source data science for machine learning projects- turn it into a hobby or side project, you can enjoy Working in within your free time
How to get a job as a data scientist?
There are a lot of varied roles in the data science Industry. Data visualisation Expert, a machine learning Expert, a data scientist, data engineer and others are a few of the many roles that you could go into. Depending on your background and your work experience getting into one role would be easier than another role.
- Be patient. You will apply for Meri hundreds of jobs before getting one.
- Prepare a lot. Not only study important concepts, programming and answering business questions, also remember that you will be an important piece of the organisation, you will deal with different people and situations, Be ready to answer questions about how you would behave in different work situations.
- People rarely associate communication skills with rejection in data science roles. They expect that if they are technically profound, they will Ace the interview. This is actually a myth.
- Knowledge of data storage techniques along with the basics of big data will make you much more favourable than a person with Hi-Fi words on the resume. It is because our organisations are still figuring their data science requirements.
Steps to how to become a data scientist
Step 1: Ask the right questions
- Am I intrigued by statistics and programming?
- Am I willing to constantly upskill?
- Do I really enjoy solving problems?
- If data science wasn’t lucrative, would I still go for it?
Step 2: Fulfill data science prerequisites
- Technical skills
- Maths and statistics, computer science engineering.
- languages like Python, Scala.
- machine learning techniques.
- SQL and NoSQL databases.
- analytical tools like SAS or R.
- Non-technical skills
- Exceptional curiosity.
- Business acumen and domain knowledge.
- Excellent communication skills
Step 3: Read the best books for data science
- Statistics and probability
- Naked statistics
- Introduction to statistical learning
- Introduction to Probability
- Practical statistics for data scientist
- Head First statistics
- Programming languages and tools
- Python crash course
- Intro to machine learning with Python
- Hands on programming with R
- Learning SQL
- Hadoop- the definitive guide
Step 4: Data science certifications
- SAS Certified Data Scientist
- Cloudera certified professional data science certificate (CCP)
- Microsoft professional program certificate
- IBM data science professional certificate
- EMC Proven professional data scientist Associate (EMCDSA)
Step 5: Responsibilities of a data scientist
- Perform exploratory data analysis.
- Process cleanse and verify the integrity of data.
- Identify trends in data and make predictions.
- Generate insights using machine learning techniques.
Secrets to succeed as a data scientist
Data science is a growing field. As individuals and organisations realize the potential applications of big data, there has been an increase in the number of people applying for jobs that are related to data science.
- Get the right amount of training
The first step to become a data scientist is education. After all, data science is a complex and broad field that branches out into subfields. Regardless of whether you are planning for a career in statistical analysis of cloud computing, quality training comprises a big factor of your potential for success.
- Gain marketable skills
Not all courses provide you with everything that you need in order to thrive in the industry. You can take up other skills that are required as you go along. At any rate, you will need to focus on foundational elements such as problem solving and analysis.
- Know where to start your career
Are you planning to work at a large company or as a freelancer? Other ways, it is important to know the best place to find jobs. Linkedin is a good start since it allows you to connect with organisations of different sizes that need help with database management for cloud migration strategy.
- Keep growing your network
Networking is a basic but Integral skill to have as a professional in the world of data science. It is your ticket to become a globally competitive individual in a job market that keeps on growing. For this reason, you need to connect with people who can become your potential mentors. other than, making a healthy habit out of attending conferences and other IT-related events.
Top data scientist jobs
Here is a list of some top companies that are hiring a data scientist in India
- American Express Global Business travel (GBT)
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