INDIA: TOP 10 HIGHEST PAYING DATA SCIENCE JOBS TO APPLY FOR IN FEBRUARY 2021

Source – https://www.analyticsinsight.net/

Analytics Insight has listed top 10 highest paying data science jobs in India that candidates should apply for in February 2021

The inflow of data has ballooned exponentially in recent years. As data started pouring into data centres in huge numbers, it opened the door for many opportunities, especially in data science. Technological changes in the data landscape left digital transformation as the only choice. As more and more companies turn towards digitisation, they seek people to fill data science and relative positions. The demand for data science practitioners is spread across the globe. These job opportunities are expected to surge beyond 2021, adding more than 1.5 lakh new jobs. For four years in a row, data science has been named the number one job in the US by Glassdoor. In a recent survey, Analytics Insight has concluded that by 2021, there will be over 3 million new job openings in data science worldwide. Demand for data-related professionals currently outweighs the supply, meaning that companies are willing to pay a premium to fill their open job positions. Analytics Insight has listed the top 10 highest paying data science jobs to apply for in February 2021.

Data Analyst

Average salary (Per Year): INR 6,35,379

The job of the data analyst is to assign a numerical value to these important business functions so that the company’s performance can be accessed to and compared over time. Data analyst jobs mostly involve looking at numbers and knowing how to use data to enable an organization to make more informed decisions.

Data Scientist

Average salary (Per Year): INR 8,15,779

Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyze, process and model data, then interpret the results to create actionable plans for companies and other organizations. Remarkably, data scientists are also analytical experts who utilize their skills in both technical and social science to find trends and manage data. The actual job involves making sense of unstructured data from sources such as smart devices, social media feeds and emails.

Data Engineers

Average salary (Per Year): INR 8,26,959

Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. Data engineers are accountable for building algorithms to help give easier access to raw data. But to do this, they need communication skills to work across departments to understand what business leaders want to gain from the company’s large datasets. Data engineers also need to understand how to optimize data retrieval and develop dashboards, reports and other visualization for stakeholders.

Business Intelligence Analyst

Average salary (Per Year): INR 5,83,784

Business intelligence analysts are proficient in computer programming languages, Business Intelligence (BI) tools, technologies and systems. BI analysts determine business-critical priorities and requirements. They define KPIs (Key Performance Indicators), implement DW (Data Warehouse) strategies, and identify BI by mining big data using advanced software and tools. The BI analyst’s primary goal is to empower decision-makers with accurate, real-time, actionable insights that enhance workflow efficiency, increase productivity, strengthen market positioning, improve the competitive edge and augment customer experience.

Quantitative Analyst

Average salary (Per Year): INR 9,67,725

Quantitative analyst or ‘quant’ is a specialist who applies mathematical and statistical methods to financial and risk management problems. Investment banks, asset managers, hedge funds, private equity firms, and insurance companies employ quantitative analysts to help identify profitable investment opportunities and manage risk.

Machine Learning Engineer

Average salary (Per Year): INR 6,71,548

Machine learning engineers sit at the intersection of software engineering and data science. They leverage big data tools and programming frameworks to ensure that the raw data gathered from data pipelines are redefined as data science models are ready to scale as needed. Machine learning engineers focus on designing self-running software for predictive model automation. They work closely with data scientists and ensure that the models used can ingest vast amounts of real-time data for generating more accurate results.

Data Architect

Average salary (Per Year): INR 1,900,000

Data architects are senior visionaries who translate business requirements into technical requirements and define data standards and principles. After assessing a company’s potential data source, both internal and external, data architects design a plan to integrate, centralize, protect and maintain them. Data architects are responsible for visualizing and designing an organization’s enterprise management framework.

Database Administrator

Average salary (Per Year): INR 4,94,678

Database administrators create and maintain databases compatible with their companies’ needs. They oversee database updates, storage, security, and troubleshooting. Database administrators ensure that data remains consistent across the database, data is clearly defined, user’s access data concurrently and there is provision for data security and recovery control.

Statistician

Average salary (Per Year): INR 5,26,829

Statisticians practice the science of using data to make decisions. They decide what data they need and how to collect it, design experiments, collect, analyze and interpret data, and report conclusions. Statisticians often work in teams, usually including professionals from other disciplines. They interpret data and communicate results to their clients, often with the aid of mathematical techniques and software.

Enterprise Architect

Average salary (Per Year): INR 31,11,000

Enterprise architects are responsible to make sure that a company’s business strategy uses proper technology systems architecture to achieve its goals. Enterprise architects have an enormous degree of responsibility and reports directly to the chief information officer (CIO). They need to keep up with the latest trends in technology and determine whether or not they would be the right fit for a company.

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