Data Scientist- New Demand at global market

Data Scientists are professionals who can analyze and explain complex digital data. They organize varying data elements with various techniques including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, visualization, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products.

To start your career as a Data Scientist, you are required to having a clear knowledge in Data Science. A Data Scientist dealing with the big data an important aspect of data science. In fact, data science is such a relatively new and rising discipline that no one can easily learn it without any training program to be become a data scientist

Demand of Data Scientist

A lot of companies and industries have dramatically increased investments in their digital platforms in the past few years. It has been estimated that by 2020, IT departments will be monitoring 50 times more data than they are today. This tidal wave of data is driving heavy demand for Data Scientist to manage these very large data sets into a competitive advantage.

The study warns there is a significant shortage of qualified Data Scientist to analyze big data sets adequately. According to the report, a shortfall of about 140,000 to 190,000 individuals with analytical expertise is projected by 2018.. The study also predicts a need for an additional 1.5 million managers and analysts by that same date to fully engage the true potential of the currently available data.

Thousands of data scientists are already working at both start-ups and well-established companies. Simply put, if any organization stores multiple petabytes of data, you’ve an opportunity there.

• Yahoo, one of the firms that employed a group of data scientists early on, was instrumental in developing Hadoop.
• Facebook’s data team created the language Hive for programming Hadoop projects.
• Many other data scientists, especially at data-driven companies such as Google, Amazon, Microsoft, Walmart, eBay, LinkedIn, and Twitter, have added to and refined the tool kit.
• Even the largest firms, such as Accenture, Deloitte, and IBM Global Services, are in the early stages of leading big data projects for their clients.

What to learn to become Data Scientist

A basic understanding of statistics is vital as a data scientist. Data science is a blend of skills in three major areas:

1. Mathematics Expertise
2. Technology Hacking Skills
3. Tactical Business Consultant
• You need to learn Hadoop Technology, R Studio, SAS Language, Excel and Tableau
• Statistical programming language, like R or Python, and a database querying language like SQL
• You should be familiar with statistical tests, distributions, maximum likelihood estimators, etc.
• You need to be familiar with the machine learning methods, like k-nearest neighbors, random forests etc.
• Having knowledge of Data wrangling
• It is important to visualize data, with the principles of visually encoding data and communicating information

Data scientist jobs responsibilities:

After learning Data Science, you will get many opportunities and jobs in various sectors and industries. There are many resources out there may lead you to believe that becoming a data scientist requires comprehensive mastery of a number of fields, such as software development, data munging, databases, statistics, machine learning and data visualization. Don’t get bogged down with all the jargons being used. Once you learn it, it’ll be much easier.

Listed below are the job responsibilities of a Data Scientist:

• Data scientist make meaningful data-like contributions to the production code and provide basic insights and analyses.
• They are responsible for creating information visually and making the patterns clear and compelling.
• They can advise executives and product managers on the implications of the data for products, processes, and decisions.
• Your job might consist of tasks like pulling data out of MySQL databases, creating advanced Excel pivot tables, and producing basic data visualizations.
• Data scientists are deals with number of activities, such as data mining and analysis, which can help businesses gain a competitive edge.

Salary Expectation of Data Scientist

If you became a good data scientist, there will many doors open to you and salary will grow automatically. Several data scientists working at start-ups commented that they’d demanded and got large stock option packages. Salaries of Data Scientists range from $85K on the average low end to $195K on the average high end.

According to PayScale, a Data Scientist earns an average salary of Rs 615,786 per year.

According to GlassDoor the average Data Scientist salary is Rs 650,000 per year.

Conclusion:

As professionals looking for job change and want to pursue better career growth, LinkedIn reveals the top 10 most promising job roles of 2017. According to them Data Scientists or Data Engineers enjoys a career advancement score of 8 out of 10 and job openings are up 85 percent year over year. Courses and books are great for developing fundamental technical skills, but many data science skills can’t be properly developed without proper training in data science course where you learn how data sets are well groomed.

If you want to start a career as Data Scientist and learn Data Science, I would recommend you to go through a structured training on Data Science. If you take up a structured training in Data Science, you will find it very easy to land up a dream job as Data Scientist.

Hope this post helps you. If you have any questions you can comment below and I will be glad to help you out.