Data scientist job roles to more than double in five years! Are you ready with the right skills?

 Digitisation has been at the forefront since the 2020 pandemic and organizations, globally, have invested in emerging technologies to augment their operations and efficiency. As this journey of digital evolution continues, data science and analytics has taken a centre stage.

Increasingly, companies are realising the importance of data to optimize their business operations. Data enables business leaders and decision-makers to take informed decisions and ensure prosperity and growth.

In fact, data science has emerged as one of the fastest-growing business segments, having witnessed over 650% growth since 2012, and expected to grow to 230.80 billion dollars by 2026.

This has significantly increased employment opportunities in the space and the demand for skilled resources. Data science-related job roles are one of the most in-demand tech jobs in the world right now and estimated to be the third-highest paying.

 Starting salaries for data science-focused job roles have also witnessed incredible growth with the average salary starting from $210,000 per annum and can go up to limitless amounts due to the potential entrepreneurship opportunity.

As more employers will continue to hire for this domain in 2023 as well, let’s take a deeper look at the top skill sets that data science candidates must have:

1. UNDERSTANDING DATA – DATA EXTRACTION, TRANSFORMATION AND LOADING

With numerous data sources and applications available, Data Scientists must know how to read and extract usable information and insights from raw data. This means they must know what the best application to use, when to use it and how.

They must be able to convert the raw data into a suitable format or structure for easy querying and analysis.

2. MINING THE DATA - DATA EXPLORATION AND DATA WRANGLING

Data analytics as a job profile has witnessed 7x growth in the last decade. An industry agnostic profile, the demand for candidates are expected to have in-depth knowledge about deconstructing and interpreting data. Post the initial phase of sorting and processing the data, analysis process is exploratory data analysis (EDA) to figure and make sense of the data, and to modify the resources to get desired answers to problems.

This process is done by observing patterns, trends, outliers, and unexpected outcomes, among others. Data Wrangling, on the other hand, is a lengthy and time-consuming process however it will help in making better data-driven judgments.

3. PROGRAMMING LANGUAGES - PYTHON AND R PROGRAMMING

Python and R Programming are the most common coding language required in Data Science roles for organizing unstructured data sets and generating necessary outcomes that are desired by companies, irrespective of their domain.

To manipulate the data and apply sets of algorithms as and when required, Data scientists should possess expert knowledge of these languages.

The demand for this skill has been high across industries like healthcare, finance, government, energy, hospitality and logistics. In the next five years, the demand for data scientist with knowledge of Python is expected to go above 10 million.

 

4. MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE

The emerging technologies to look out for in the next few years, data science professionals adept at or building ML and AI technologies stand out and are treated as royalty in the tech world.

With a clear understanding of machine learning and AI concepts, an individual can work on different algorithms and data-driven models, and can simultaneously handle large data sets such as cleaning data by removing redundancies.

This allows significant optimisation and brings in critical efficiency needed by companies to reduce costs and ensure profitability.

5. STATISTICS AND PROBABILITY

To perform tasks and execute to get the desired output, data scientists are expected to have a strong command of numbers, statistics and probability.

Before creating high-quality models, it is required to understand these concepts without which making senses of reams of data would be impossible.

As the demand for data scientists continues to increase exponentially, it is critical for the industry to have access to skilled talent. Aspiring candidates need to focus on acquiring the required skill sets and continually upskill themselves.

In-demand roles that require specialization include data engineer, AI engineer, and business analyst – salaries for these roles average around Rs 45 lakhs and are climbing fast.

 Source: India Today