Data Science - A Career With Wide Range Of Opportunities
The data analytics term is used for relatively lower-paid jobs, focused on routine inspection of data, its visualization and report generation. Majority of jobs in this category carry a salary range of Rs 6.00 lakh per year or below. On the other hand, a majority of data science and data engineer jobs carry a salary of Rs. 8.00 lakh per year and above
Recent years have seen many breakthroughs in the field of communication, scientific investigation, automation and integration of routine appliances (IoT). These advances have impacted almost all aspects of human activity ranging from the interpersonal to the mass communication, business practices to manufacture, research to education and learning process. One fundamental aspect of this change is the flooding of our ambiance with information of all kinds. Scientists, who used to look at one or more gene at a time can observe biological activities of molecules in a high throughput manner. Financial data that used to get lost in the paper trail is now available to access, process and analyze by the click of a button. The interactive online video streaming and live sessions have replaced the painstaking delivery of messages written on pieces of paper. A flurry of information surrounds us in the form of structured and unstructured data. Big data-primarily characterized by the so-called 3 V’s namely Volume, Variety or heterogeneity and Velocity or dynamic growth- is the buzzword in all aspects of professional discourse. Data inventories of the industry, the academic laboratories, public offices and individual devices are growing exponentially. This scenario has created career opportunities at multiple levels of expertise and application. Here, we cover three major categories of career opportunities in this exciting field viz. Data analyst, Data scientist and Data engineer. Even though the distinction between the three categories is debatable and not always accurately utilized by the various stakeholders, the job opportunity trends can give us some insights. A survey of the vacancies available in India through online recruitment website indeed.co.in has revealed some interesting trends. Within these three categories, the number of jobs posted during the last two weeks at the time of compiling this report showed the highest number of 1334 jobs for the data scientist, followed by 628 and 425 jobs for data engineer and data analyst (see illustrations). The data analytics term is used for relatively lower-paid jobs, focused on routine inspection of data, its visualization and report generation. Majority of jobs in this category carry a salary range of Rs 6.00 lakh per year or below. On the other hand, a majority of data science and data engineer jobs carry a salary of Rs. 8.00 lakh per year and above. As shown in the illustration the three types of job openings are not limited to any specific profile of an employer, as hiring offers come from diverse fields such as software development, commodity trading, finance management and they are employing data professionals at all levels. It is also noted that most of these jobs in India are concentrated in five cities, well known for their scientific and Industrial edge viz. Bengaluru, Hyderabad, Pune, Mumbai, and Chennai. The number of jobs in this field is likely to continue to grow rapidly. It has been reported that 59 percent of all Data Science and Analytics (DSA) job demand is in Finance and Insurance, Professional Services, and IT and that the Annual demand for a data scientist, data developers, and data engineers will reach nearly around 7.0 lakh openings by the end of this decade.
Skill sets and qualifications needed for data science career:
As stated above, people with diverse skill sets and academic qualification can enter into data science career. Data analyst needs the most basic skills and qualifications as some of these jobs are available to individuals with even MS Excel level data analytics. On the other hand, data scientist and data engineers jobs typically require at least a Master’s level qualification and much deeper skill sets such as machine learning, cloud computing, and Hadoop related experience. R and Python remain the most popular skills for data scientists and Hadoop, Apache Spark, SQL, NoSQL, MongoDB are very much in demand for data engineers. Linux remains the most popular operating system for data science and engineering, whereas Windows PCs are widely used by data analysts.
Where to study:
Many data science students take to online courses such as Coursera, which has a wide range of data science related courses. Institutes all over India regularly organize a number of workshops and short-term courses on various aspects of Data science. In India, leading institutions have risen to the occasion and started programs of study, most of which have been done during last few years. In the field of business and finance, a Business analytics and management course are offered by IIM Bangalore. IIM Calcutta, ISI Kolkata, and IIT Kharagpur, jointly offer a Postgraduate Diploma in Business Analytics (PGDBA). A PG Diploma Program in Data Analytics is offered by IIIT Bangalore. Courses offered by several private institutes have also drawn high ratings. Courses with a special focus on non-business aspects of data have been started. Of them Jawaharlal Nehru University (JNU), with support from Department of Biotechnology (DBT), India has initiated a course focused on Biological data. Indian Institute of Science (IISc) has replaced their traditional M.Tech. program in computational science with an M.Tech in Computational and Data Science. This course offers specializations in areas such as Bio-molecular Computation, Medical Imaging and other aspects of Scientific Computation. In general, other than business and finance, the Biological data, Geographical information systems and weather forecasting remain some of the top data analytics themes at the level of research and tertiary education, not covered specifically in this report.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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