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According to a survey conducted by IBM, there will be an increase in job openings by 364,000 to 2,720,000 openings in the year 2020. Furthermore, the unstoppable rise in demand for data scientists will reach approximately 700,000 openings in the same year.
Jobs in Data Science are currently reigning the market such that Glassdoor has declared it to be the number 1 job on its website. Furthermore, the data science openings are open for 45 days, which is five days more than the regular job market!
Finance and professional services are the main demand zones for data scientists. The demand in these fields is 59% of the total demand for data scientists, which is the highest among all the industrial sectors. The Finance Sector accounts for 19% of the openings whereas professional services account for 18% and IT sector holds 17% of the total.
The demand for data scientists and advanced analysts will skyrocket in the year 2020, with a projected demand spike of 28%. Considering the rarity of ‘pure’ data scientists, industries are paying premium salaries to those who have the right expertise.
Data Science is a huge field. You can be a Data Analyst if you have a non-technology background in mathematics, statistics or quant. You can be a data engineer if you are a technology major with a background in programming and coding.
A strong educational background is needed for developing and absorbing the cross-disciplinary knowledge that Data Science professionals need. A bachelor’s degree in computer science, statistics, mathematics, engineering or related fields will do the job for you.
Get a vendor-neutral, cross-platform, third party certification in Big Data Analytics or Big Data Engineering (your choice!) from an internationally respected body.
If you want to stand out, get a serious certification from a proper standards and certification body. Certificates from online training companies are very common and everybody seems to have them, so employers do not respect them. They work only if you just want to have some knowledge. But if you want to make a career in data science, you need a credible, respected qualification.
Knowing R programming is essential because R is cut out for statistical analysis done in data science. Learning R becomes easier if one knows SPSS. Good certification programs like ABDA™/SBDA™/ABDE™/SBDE™ include this in their curricula.
Python is the most common coding language deployed in data science, though Java, Perl, and C/C++, too have wide circulation, no doubt. Similarly, SQL is important, though NoSQL is doing the rounds these days. Good certification programs like ABDA™/SBDA™/ABDE™/SBDE™ include this in their curricula.
Knowing Hadoop, Apache Spark, Hive, Pig and cloud technologies is a strong must because data scientists must know the tools of sharing vast amounts of streaming data, and also techniques of data exploration, data filtration, data sampling, summarization and data visualization. Good certification programs like ABDA™/SBDA™/ABDE™/SBDE™ include this in their curricula.
Knowing AI, Neural networks, supervised machine learning, decision trees, logistic regression, reinforcement learning, natural language processing, outlier detection, computer vision, recommendation engines, survival analysis and others enhances attractiveness for the most challenging Data Science jobs. Good certification programs like ABDA™/SBDA™/ABDE™/SBDE™ include this in their curricula.
Data Scientists must be able to visualize data using data visualization tools such as ggplot, d3.js and Matplottlib, and Tableau. Good certification programs like ABDA™/SBDA™/ABDE™/SBDE™ include this in their curricula.
Remember, data science has numerous types of jobs and roles, and newer ones keep getting added as technologies evolve. Data Scientist/Data Architect/Chief Data Officer and others are positions considered to be the most senior ones today. The following are the typical four types of Data Science jobs one may want to pick from:
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