The job of a data scientist job is more lucrative and highly paid in the job market now. The companies, as well as data scientists both, try to hire and get hired. The policies of companies and social statistics need organized and conclusive data to make decisions.
When we hear, “In the 21st century every third person will be diabetic,” and “It is found that most divorces are taking place on a Monday,” these conclusions are derived at by scrutinizing bulk data. This makes the data scientist have a crucial role in an organization.
To get hired, one must have a strong portfolio. Companies generally prefer candidates with a Master’s degree in data science for data scientist managerial positions. There are other positions, such as data engineer, machine learner, data analysts, etc. For each position, the experience, as well as a degree or a diploma, is preferred. To have a degree and experience is difficult because either you can enroll in the course of a data scientist or you can join a company for some different job. To build your portfolio with both the things, you can earn and learn. You can opt for an online master’s in data science.
Data scientist jobs require programming. Learn R programming, Python, Spark, Machine Learning, etc. The online course offers you these subjects through conferencing, podcasts, webinar, etc. You can discuss each case and solution thereto. Through periodical appraisal, you can find out how much you have mastered. Get as much as the practice of solving and scrutinizing data, making reports, presentations. If your job is in the same field, try to get more into statistics to strengthen your portfolio, because recruiters are more interested in how you have practically worked on data science.
Even if you can answer all question about R, Python and remain blank about any situation to deal with, your chances will be nil. You should have at least 3 or 4 assignments to show about real life work, how to deal with a complicated situation, how to deal with new data, and how to explain hard concepts to a manager. Have your code samples ready on GitHub and participate in Kaggle competitions.
Be patient. Apply to as many jobs as possible, and prepare a lot, be ready to answer all questions and visualize how you will behave in different situations. Data science is a new concept to you as well as the recruiter. You may be rejected if you cannot convince them about the knowledge you have.
Don’t worry. Every interview will teach you a new way to get hired. Analyze yourself from your experience and learn from mistakes. Make your portfolio stronger with statistics, math, and machine learning. Keep learning about programming in different languages. Accustom yourself with various database software. It is not just about collecting data, but also about becoming an expert in data munging and visualizing. You should also be an expert in reporting data as your additional skill, which should prove beneficial to companies where you are applying for data science positions.
Apart from programming languages, learn something special to stand apart from the herd. The usual qualifications may give you a moderate job, or even you may not also get competing with hundreds of common recruits. Being uncommon and having a particular skill will land you a job you want. Read the newspapers, analyze news, and write blogs about it. Make a habit of writing blogs, creating conclusion posts on blog posts or LinkedIn. Join the community of data scientists and show them the papers/blogs you have written. Ask their opinions and feedback while discussing the nuances. Build relationships with them to keep updated about current scenarios.
Also, build your own data sets. Search the web for scraping libraries or unique APIs to make your customized databases. Companies will appreciate the different view and unorthodox methodologies to grow their revenue.
Data science might look hard on the outside, but it is an investment which will net you significant returns. Because big data is here to stay, you might even say it is a gift which keeps on giving.