Organizations are looking to create a skilled talent pool that can provide technical expertise and move faster in the competitive environment

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May5, 20214 min read

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In recent years, data science has emerged as one of the most prominent career choices for fresh graduates as well as working professionals across hierarchical levels. The demand for skilled professionals in the field of data science has grown remarkably owing to the urgent need for strategic decision-making tailored for specific regions. Organizations are looking to create a skilled talent pool that can provide technical expertise and move faster in the competitive environment. According to Han Digital, the demand for data science experts has grown across sectors, IT services companies employ the majority (40 per cent) of the data science talent pool from India, followed by global in-house centres or captives in India with a 30 per cent market share. Here are key reasons for this growing demand.

Data has become the backbone of business decision making: Organizations generate a huge amount of data regularly. According to estimates, the total amount of data created, copied, captured and consumed in the world is likely to reach 149 zettabytes by 2024, as compared to two zettabytes generated in the year 2010. Data science has proven to be a powerful tool to extract meaningful insights from this large chunk of data. These insights help organizations in determining any prominent changes that are to be made basis the changing consumer behavior, shortcomings of previous solutions, forthcoming challenges and competition analysis. Most of the organizations today rely on strategic decisions backed by technology. This has become a major factor that has fueled the demand for skilled talent in the field of data science.

Dearth of skilled talent pool: While the demand for professionals adept in data science skills is at an all-time high, there is a major demand-supply gap due to the non-availability of skilled talent. In order to meet this acute shortage, many organizations are investing in training their employees through tie ups with edtech companies as well as launching internal training programs.

Highly lucrative career opportunity: Owing to the massive dearth of skilled professionals in the domain, organizations are willing to pay a premium and offer long-term incentives to attract and retain talent. According to Michael Pages 2021 India Talent Trends report, professionals with 3-10 years of experience receive an annual salary ranging between INR 25-65 lakh and those with more experience can command packages upwards of INR 1 crore. It further mentioned that experts with more than 15 years of experience can receive a salary up to INR 1.8 crore.

Omnipresence of jobs: Whether large or small, organizations irrespective of their sizes and industries are banking on technology for better efficiency. Industries such IT, BFSI, retail, healthcare, telecommunication and e-commerce are actively hiring data analytics professionals with salary increments to the tune of 35-45 per cent. Data science professionals today act as the backbone for organizations to harness data and meet their strategic goals.

Low entry barriers for existing professionals: Data science domain comes with very few entry barriers and allows for professionals from diverse backgrounds to join the workforce. It demands candidates to have proficiency in technical as well as business skills and with the availability of quality learning programs, anyone with the willingness to learn has the opportunity to enter this domain. The secret sauce lies in learning the required skills as well as improving the existing ones. Individuals can acquire good statistical and data mining techniques, programming languages, machine learning and advanced analytics by enrolling for a high quality upskilling program.

A large selection of roles within the field: The field of data science has a lot to offer to freshers and professionals. One may choose to opt for a job role based on their interest as well as experience level. Some of the job roles that are high in demand include data scientist, data architect, BI engineer, business analyst, data engineer, database administrator, data and analytics manager.

With the growth data science is witnessing across the globe, there are massive job opportunities available across industries resulting in the huge demand for skilled talent in this domain. Anyone who is looking to create an impact in this field should identify the skills required and should focus on acquiring the same by opting for the right learning program that best suits their profile.

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Reasons Why Data Science Will Continue To Be the Most Desirable Job Of the Decade - Entrepreneur

When Raj Desai G21 decided to leave his home country of India to attend graduate school in the United States, he looked for one thing in particular: practical experience. He graduated in 2019 with a Bachelors degree in computer science. Still, after hearing about his friends experiences studying abroad, he felt that the iSchool was the right place for him to get hands-on experience in the data science field.

Desai got involved in extracurricular activities, participated in faculty research, and started building his Masters program for Applied Data Science. He was also excited about the opportunity to diversify his academic interests by taking a wide variety of courses.

When I was an undergrad, I didnt get to choose any of my courses, said Desai. Now that Im at the iSchool, I can build a portfolio of courses that Im interested in, and even take classes outside of the iSchool in computer science or at the Whitman School of Management, he said.

One of Desais most significant projects outside his coursework is his role as a Graduate Faculty Assistant working with professor Bei Yu in text mining. The research focuses on building a model that explains peoples health beliefs about COVID-19 by annotating text to look for patterns. Desai is working on building a data set as part of the model to predict individual views about the pandemic.

His role as a faculty assistant also requires him to work with students taking courses in natural language processing and answering their text mining questions.

This job taught me how to help other students get into the data science field and use their projects we work on in class to get jobs and internships, Desai said. I love interacting with the students, even with our current virtual format during the pandemic.

This spring, Desai worked for IPwe, a fintech startup based out of Dallas, Texas, as a data science intern working on extracting genomic sequences from thousands of documents. He then mapped this information with the organisms. He worked on another project based on financial data using SQL.

Desai also worked on a research project at the iSchool during the summer in which he analyzed more than 2000 documents to model energy trends in the United States. He simultaneously completed a summer internship at Tangible AI, a nonprofit startup based out of La Jolla, California. While his summer consisted of 80 hour work weeks at times, Desai is grateful for the experiences because he believes it helped him get ahead in his field.

He also gained practical experience in data analytics by working as an analyst for iConsult, the iSchools collaborative that connects students with real-world clients who need help with digital transformation projects. Desai worked on a project in the fall that built a chatbot that helped individuals with disabilities find jobs that match their skill sets. His role was to clean a data set using Python about what types of jobs are available for people with disabilities and what those individuals feel are their most essential skills. He then created dashboards and data visualization that the chatbot used to connect users with job opportunities.

All of these experiences have helped Desai prepare for his current job search. He will graduate in May and hopes to find a role as a data scientist or a data engineer. His work as a faculty research assistant and at iConsult has developed his interest in working in a position where he can use machine learning in the initial stages of preparing data for analysis.

The faculty and staff have been so supportive of my job search in all aspects. They are so enthusiastic, and many career center staff members like Jeffery Fouts are always willing to help me prepare for interviews, Desai said.

Desai isnt sure exactly where hell end up after graduation, but he feels very optimistic about improving economic conditions amid the ongoing pandemic. He has many interviews lined up for full-time positions post-graduation. No matter where he lands, Desai is confident that his skills and experiences in data science from the iSchool will help him build the career of his dreams.

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Personalizing the iSchool Experience with Electives and Faculty Assistantships - iSchool | Syracuse University - Syracuse University News

Speaking with Insurance Business, nib chief information officer Brendan Mills (pictured) noted: Weve focussed quite heavily over the last little while and continue to do so which is what were doing here with these roles on building stronger and deeper capabilities across the business around machine learning, data science, and the like.

Its a real focus on data and making sure that data is seen as a first-class citizen, and that we use data to be better able to predict and inform our members healthcare and well-being needs. So, thats the overarching driver. And, within the business, were also looking at where else we can use data engineering and machine learning capabilities across sales and marketing, retention, and claims processing.

In fact, nib is presently doing some work in the area of claims processing around using machine learning. Essentially, the capability being built group-wide is aimed at serving the insurer fairly well not only in being able to improve the member experience, but also in reducing nibs cost base in time.

While theres a lot of work ahead, the whole prospect surrounding the payer-to-partner transition is leaving the chief information officer stoked.

To really move closer to our members healthcare needs and to be able to apply data insights be it through traditional data engineering or through more contemporary methods around data science and machine learning is definitely the most exciting opportunity we have, I think, as a business, said Mills.

The challenge, though, is debunking peoples perceptions around the use of data.

The nib executive explained: Sometimes theres a view that with data we will increase someones premium or we will deny the cover or whatever. In our situation, because of the regulations we operate in, thats actually impossible to do. We cant charge someone a different premium or deny them cover; we have a mechanism called community rating, which prevents us from doing that.

What were really trying to do is make sure that as someones health partner, we really look at how we leverage the data to better serve them, stressed Mills, be that through using data to identify claims patterns that might ultimately allow us to offer them a health management programme or be that prediction of future episodes of care that they might need.

Theres no doubt that with the right harvesting and engineering of data, well be able to get closer and closer to our customers and better meet their needs, which I think is a pretty exciting proposition.

Whats crucial, he said, is getting that careful balance between people sharing data and people being more willing to give data in exchange for value.

As consumers, were quite often prepared to share our data in exchange for something, the chief information officer went on to illustrate. So, we share our data with Facebook in exchange for some sort of social media experience and connectivity with friends and family, and advertising or posting.

I think for us its about creating the right opportunities, the right products and services, the right platforms for people to then want to engage with us, to share their data with us, to then give them that value back.

Mills believes whats important is creating that right value exchange and being able to demonstrate, through real-world use cases, that the products and services are indeed valuable to the consumer.

He told Insurance Business: I think thats really where our opportunity and challenge lies, is that once we nail that and get that right, well have a far more open dialogue. Weve got some good programmes in place already, and weve started to work closely with a lot of our customers around health management programmes.

Weve set up a joint venture, in addition to the main part of the business, which is focussed on delivery of a lot of these clinical services. So, were well on the way, but we have a lot of work to do yet.

If you ask Mills, though, hell say that the work actually never stops.

I dont feel like you ever start and stop with these things, he asserted. The way I like to think about our investment in technology and business process reengineering, and the experiences were trying to create, is that its pretty much a continual evolution of what were offering.

I wouldnt like to put a timeline on it per se, because I just dont believe youre ever finished. As we get more and more feedback from our members and our customers, well adapt and pivot and align the experience to the feedback were getting along the way.

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nib chief information officer on pretty exciting proposition - Insurance Business AU

People wait in line to receive the COVID-19 vaccine in Mumbai, India, on 29 April.

By Priyanka PullaMay. 4, 2021 , 12:10 PM

Reporting for this story was supported by a journalism grant from the Thakur Family Foundation, which has not influenced the contents of this report.

Indian researchers say they urgently need better access to data collected by government agencies to help them understand and fight the countrys devastating second pandemic wave. An open letter published on 29 April that has 740 signatories so far asks the government for access to databases on COVID-19 testing and genomic sequencing and urges it to remove other obstacles to research.

There are currently so many hurdles and so much paperwork around accessing these data, says Partha Pratim Majumder, a genetic epidemiologist at the National Institute of Biomedical Genomics in West Bengal and one of letters signers.

The Office of the Principal Scientific Adviser to the Government of India, K. VijayRaghavan, released a note the next day acknowledging the problems and promising to increase access. Our broader research community needs to be much more facilitated by our research agencies, the letter said. But some scientists are skeptical that the situation will improve quickly; the note was low on details and previous requests for data from government agencies have often gone unanswered, they say. Why the Indian government is so reticent to share data is unclear.

The government has collected detailed data on some aspects of the pandemic. For example, the Indian Council of Medical Research (ICMR), the countrys top medical research agency, captures demographic details such as age, location, and health status of everyone who submits a sample for a COVID-19 test. The data could help answer key questions, such as whether people with certain concurrent illnesses are more likely to have worse outcomes and whether vaccines are working, says Gagandeep Kang, a public health microbiologist at the Christian Medical College, Vellore, who also signed the letter. Lots of people want to know, for instance, what mortality is by location, and whether it differs between rural and urban areas, she says. This speaks to the kind of care people are getting.

But so far, scientists say, ICMR and other government agencies have dragged their feet on responding to requests for access. That has forced several groups building computer models of the epidemic to rely on public domain data, which are aggregated by state but lack granular details such as breakdowns by district, age, or gender, says L. S. Shashidhara, a developmental biologist at the Indian Institute of Science Education and Research, Pune. Even modeling groups advising the Indian government on its COVID-19 response policy often dont have these data, Shashidhara says.

Scientists also want access to more viral genome sequences generated by the Indian SARS-CoV-2 Consortium on Genomics (INSACOG). Established in December 2020, the consortiums stated goal is to sequence 5% of all new SARS-CoV-2 cases in the country, which is important to keep up with the spread of new virus variants. INSACOG has had a slow start, with just over 15,000 samples sequenced by late April, out of about 5.9 million new cases India has seen since January. And just 6200 sequencesfewer than halfhave been deposited in GISAID, an international database, during this period.

In February, INSACOG identified a variant, later christened B.1.617, which was growing in frequency in Maharashtra at a time when that state was experiencing a massive outbreak. B.1.617 has spread to several other countries, including the United Kingdom and the United States. But INSACOG has yet to share its analyses of whether the variant is more transmissible or more virulent. We need multiple pairs of eyes need to look at this data, instead of just one, Majumder says.

The authors also ask the government to remove obstacles that prevent INSACOG from stepping up the sequencing pace. INSACOG scientists currently have to jump through several bureaucratic hoops to import reagents, plastics, and other key materials. The measures, designed to protect Indian industry, are ill-advised during the coronavirus surge, says Rakesh Mishra, a genomicist at Hyderabads Centre for Cellular and Molecular Biology, one of 10 INSACOG labs. Its like taking a blanket away from a person in winter because the blanket is imported, he says.

The note released by VijayRaghavans office says government agencies will immediately highlight mechanisms of research access to already available datasets and put in place access to new datasets as they are formed. It also says the government will remove import bottlenecks and INSACOG will involve more teams in data analysis, bioinformatics, and decision-making.

Although some scientists welcomed the quick response, others say the letter is too little, too late. The note only says that government agencies will facilitate data access, Majumder says. The question is: when? Time is of the essence. And promises made in the past by important government functionaries have often not been fulfilled on time.

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'There are so many hurdles.' Indian scientists plead with government to unlock COVID-19 data - Science Magazine

While data science is not a new term, and was growing in importance in the last several decades, it has gained currency more recently as enterprises have now become awash in a sea of data both small data sets as well as the big data generated by mass-scale applications. The global pandemic further proved the importance of managing data and extracting insights from the large volume of data generated daily to drive business decisions. Despite the collapse in the job market brought about by the pandemic, the demand for data scientists globally as well as in India continues to remain high.

In a recent interaction with CXOToday, Satish Pala, SVP of Digital Solutions at Indium Software, explains why data scientists are crucial to business growth and innovation. He also sheds light on the impact of the COVID pandemic on the Data Science job market, current skill shortage in Data Science and the way forward to reduce the skills gap.

Why do you think the role of data scientists is becoming more relevant than ever today?

Due to digital adoption over the last 5 years by enterprises, we have large volumes of data being generated and processed. In addition, user-generated data through social media and mobile apps has increased exponentially. With such data sets being available, we can derive actionable insights and predictions for almost any business, from content/product recommendation to automated self-driving cars to personal assistants, etc.

While data growth is exponential, the recent developments in advanced analytics have increased the potential to generate unimaginable insights by data scientists. Some of these technologies include Google powered TensorFlow, OpenCV, Fast text by Facebook and BERT based models by Hugging Face which powers document classification and translation. Along with the software capabilities, the hardware availability like GPUs and on-demand cloud services have made solving AI & Data Science problems easy, efficient, and quick. As a result, companies are in desperate need of data scientists, to be one step ahead of the competition.

How important is the Indian market for data scientists in terms of education, hiring?

India is among the top 5 data analytics markets in the world in terms of data generation, consumption, and services. This sector is expected to be around $15 billion by 2025. Specialized courses in Statistics and Mathematics are available in India, which are the foundations to become a data scientist. Universities also offer bachelors and masters degrees in data science covering the foundations and programming in R, Python, and other languages.

India provides a good number of data scientists when compared to other countries, only next to the US, however, there is a lack of data scientists in general. There were close to 90,000 unfilled data science job opportunities in India in 2020. As a result, India Inc. is trying to build data science capability from within as well as partner with learning institutes. Some of the top IT cities that create the maximum number of jobs include Bengaluru at around 25% and Delhi and Mumbai at around 20% respectively.

What was the impact of the COVID pandemic on the Data Science job market?

COVID-19 pandemic has completely shaken and disrupted businesses across the globe. Most of the businesses that have traditionally been run from a local and on-premise data center set up have been forced to move their businesses to the cloud to scale rapidly. Also, there is an increase in digitalization like e-commerce portals and mobile apps. As a result, we have a lot of data being generated, stored, and accessed. Once any business has these data sets, there is a huge potential to leverage these data sets and generate actionable insights for their business. Hence, there are many opportunities for data scientists. The Data Science job market is pretty hot and has actually spiked a lot in the last year.

What are the current challenges faced by Data scientists?

First of all, there are no clear set of expectations from a data scientist as the realm is vast. For example, Data scientists could vary from basic python developers to statisticians to advanced mathematicians. For example, a data scientist could be a Python developer who works with data (with SQL/Spark) or Statistical analysis or Machine Learning or Deep Learning or Computer Vision (OpenCV) or Data Analytics or Data Visualization.

Secondly, theres a lack of clarity on where to start. With the wide set of Data Science skills, its quite difficult for aspiring or even experienced ones aspiring to be data scientists to choose one or more skills to work and stick with.

Finally, I would say, experienced Data scientists are still limited in number when compared to traditional computer engineers. So, the Data Science communities and forums may not offer the same support and content for data scientists to refer to.

Do you see a solution to the current skill shortage in Data Science? How can industry-academia partnership help?

Yes. These days, there are a lot of online courses as well as university programs that are already teaching Data Science not only as a course but also as a special graduate program. Industry-Academia partnerships will help speed up. Some of the Industry players are partnering with universities to design courses, case studies and projects.

How can governments encourage more students to Data Science?

Governments can encourage more students to Data Science in three ways:

1)Demonstrate AI, ML and Data Science based outcomesin government initiatives like Digital India, UPI, etc.

2) Create Job opportunities in Data Scienceeither for the Government or facilitate through private players.

3)Focused Learning Many jobs are going to get automated in the future because of AI, so the government can take measures in upskilling people with mundane jobs through National Skill Development Centres and conducting short terms courses.

How can data scientists upskill themselves in times of pandemic?

Data scientists are crucial to business growth and innovation and need constant upskilling especially in the current data landscape. Data Scientists can register in online tech learning platforms which have a lot of real-time and video recorded courses related to Data Science. Data Scientists require a lot of practice to apply theoretical knowledge on algorithms and programming. One way to achieve this is by solving problems in online Data Science competitive platforms. They provide data sets as well. Another way is to look out for Data Science hackathons to solve problems.

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Data Scientists are Crucial to Business Growth and Innovation - CXOToday.com