As a data scientist you are required to break down large amounts of data into utilizable knowledge and develop software and algorithms in order to assist companies and organizations to gain optimal operations. You would use scientific processes, methods, algorithms and scientific systems to extract information and facts from unstructured and structured data processes.
Are you eligible to become a Data Scientist?
To get a job in the field of data science:
- You will need a graduation degree with knowledge of computer programming languages such as python, R etc.
- You must possess good analytical skills.
Skills that employers look for in data scientists.
In order to explore the field of data science, you need various technical and non-technical skills.
Technical skills Non – Technical skills
- Python (Programming Language) 1. Statistics
- R (Statistical Programming Language) 2. Mathematics
- SQL (Structured Query Language) 3. Analytical thinking
- Big Data
Now that you know the technical requirements for a data scientist, how do you get your first job as a data scientist?
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Here is the method to follow to get a job in the field of data science:
1. Build a portfolio and resume
Your resume should list all the skills that you have acquired related to data science. Mention all the projects that you have contributed to. It should mention internships and any volunteering work that you have done in the field of data science.
2. Register on job portals and upload your resume
Search for jobs on job portals. Recruiters search for potential candidates on job portals. Read job descriptions for entry-level jobs and include the related keywords such as Python, SQL, Java in your resume and the keyword section in job portals so recruiters can find you using the keywords in your resume. Check the regular notifications from the job portals and apply for the positions.
Ask your friends and family members who are working in the field of data science to refer you for openings in their company. There are more chances of securing an interview with referrals than applying on job portals since companies trust their employees and consider the candidates referred by their employees.
4. Be an active participant on Kaggle
Kaggle is an online community of data scientists. It is a platform that provides powerful resources and tools for new data scientists. Kaggle provides free courses on Python, Machine Learning, Data Visualization, SQL etc. Kaggle holds regular contests for data science projects. You can participate in these contests to gain hands-on experience in data science projects and gain insight into real-world projects.
5. Write blogs and contribute to scientific publications
Writing articles and blogs allows learning about data science concepts thoroughly. By writing blogs, you will develop the skill of explaining data to the general public in simple terms, which is essential for a data scientist. Articles that you write form a part of your professional portfolio, and it gives recruiters an idea about your comprehension of data concepts
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6. Work on independent projects
Data science jobs require experienced candidates, and it is difficult for you to gain experience before you can get a job. So work on your own independent projects which will give the required expertise,
and it is something that you can showcase to your potential employers.
7. Consider internship
As an intern, you would be allowed to work on data science projects in a company. It is an excellent way to gain hands-on experience in data science, and if your manager approves your work and is impressed by the way you work, then there is a good chance for you to get recruited as a full –time employee. If you cannot procure an internship, volunteering provides you with the required experience for a job in data science.
Networking is essential in today’s corporate life. It is essential to have contacts and grow your contacts to secure your first job as a data scientist. Stay active on LinkedIn. Share your knowledge, the projects you have worked on and participate in the data science community discussions. Share posts on your relevant field. Comment on the posts shared by people working in your area, and you may get noticed by potential recruiters in data science.
9. Prepare for the interview
Once you get an opportunity to attend an interview, take it seriously and prepare for the interview. If you are nervous about the interview, have a friend give you a mock interview so you get the feel of an interview and get over your nervousness. Companies usually conduct written aptitude tests to check mathematical ability, logical reasoning and communication skills. An aptitude test is the first step in an interview process; hence you should practice aptitude questions from books or take aptitude tests available on the internet. Read about the standard HR interview questions and think about how you would answer those questions and finally brush up on your programming and analytical skills.
10. Appear Presentable
When you appear for the interview, make sure that you are dressed professionally, look presentable and confident.
11. Follow-up on the interview
It is not a requirement, but it is polite to write an email to the interview explaining that you are thankful and appreciate the opportunity to interview them. Thank the interviewer for his time, and send him your best wishes for finding the right candidate for the position. It may create a favourable opinion of you.
There were around 93,000 vacant data science jobs in India in August 2020. Even with the Covid-19 scenario, the demand for data scientists is increasing. Data scientists earn a competitive salary. A data scientist in the entry-level earns around Rs. 5,00,000 per annum. A senior data scientist with 1 to 4 years of experience earns about Rs. 6,10,000 per annum. So there are plenty of jobs and opportunities available for data scientists. With the right set of skills, knowledge of programming languages, analytical mind and networking you will be able to procure your first data science job. It is a field that provides enormous opportunities to learn, and it provides good chances to grow within a company.
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