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How has Covid-19 affected the demand for AI, data scientists and their skill sets?


Wanna become a data scientist within 3 months, and get a job? Then you need to check this out !

Four data scientists share their views…

By Yasmin Chamchoun

Inevitably, businesses world-wide have had to make major adjustments due to Covid-19. This has included forced closures, a freeze on recruitment, staff cuts as well as postponing investments in areas such as AI and technology. In recent years, the ‘data scientist role’ is thought to have been one of the most highly sought-after professions by employers. But with the outbreak Covid-19, is that still the case?

One thing that is for sure, in order to survive these challenging times businesses will need to ensure accurate forecasts and future simulations are mapped out. To make this happen they may need the powers of AI and a good data science team now more than ever, to gather and analyse the data needed in the right way. This will then allow them to identify and resolve critical problems helping the business to adapt and then move forward.

How can AI tools be leveraged?

In the sale and business development side of things, AI tools and hiring a good data scientist can be particularly advantageous. AI-powered sales performance solutions can provide the sales team with data on which consumers are most likely to buy which product/service hence allowing them to direct their focus and outreach to them. This data can be gathered by looking at consumers previous buying habits and searches.

AI algorithms can also be generated to manage employee schedules. With a lot of employees now working from home, AI algorithms can help identify when and which employees can return to work whilst still ensuring social distancing measures are met. This can be fulfilled by inputting data such as employee location and their proximity to work, the means of transport they use to come to work, pre-existing health conditions and other vital information.

Additionally, one of the main obstacles businesses especially the retail industry has encountered is maintaining a high-level of customer support and facilitation. Working from home is now the norm and face to face interactions are almost non-existent. The usual customer support that was instantly available whether it was over the phone or face to face is now limited, resulting in longer response times and overall customer dissatisfaction.

This is where AI and automated customer response tools have provided a fast and effective solution. Chatbots via live chat on their website, SMS options and social media messaging are being incorporated across various industries. This has helped accelerate customer support and eliminate the long waits for emails to be responded to, calls to be answered or the in-shop customer support desks to reopen.

The use of automated FAQ help and support feature is also appearing valuable, allowing consumers them to find answers for themselves quicker and efficiently. This tool offers answers to the most common questions and problems which consumers have previously raised and then an in-detail guide on how to solve it.

Whilst most industries have suffered due to Covid, the take-away and food industry has thrived by making use of AI/ML tools such as food delivery aggregators. Data is being gathered on which restaurants or cuisines appeal to whom and their proximities. This has then allowed them to promote their food deals via push notifications and other digital marketing methods to customers that are most likely to order. The consumer can then get a real live status on where their delivery is and estimated time of arrival.

So, what do the data scientists think?

Here four data scientists, who are currently working in the field provide their outlook.

Adnan Yunus, Chief Data Scientist, OpusAI

How do you think Covid19 has affected businesses adaption of data science/AI? Has the adaption been hurried or delayed?

“Business were forced to be conservative in their spending towards AI adaption. I believe the general effect was negative. Generally, the progression was negatively affected. There were sectors closely tied to health-tech which did benefit in the

short-term. However, for non-health-tech business, the lockdowns, the mandatory closures and the media-hysteria projected an uncertain future which lead to pessimistic spending.”

How has the demand for data scientists and their skillsets changed since Covid19 and why is the data scientist role still crucial?

“Today it is more important than ever for an organization to integrate data-driven-insights as part of their key decision-making process to tackle the volatile growth and competitor landscape.”

Rahul Agarwal, Data Scientist, Writer at https://mlwhiz.com

How do you think Covid19 has affected businesses’ adaption of data science/AI? Has the adaption been hurried or delayed?

“In my view, COVID19 has forced us to refocus on our ways of working and looking at data. What happens when a Black Swan happens — How do we make our models even more resilient to a novel event? What is more critical — Economic Gains or our Customer?

As for the adaption of Data Science, I think it dropped in the initial days when COVID stuck, but as companies are now getting more and more accustomed to the current environment, the adaption is increasing, and AI has become increasingly more important. We have reached an inflection point. New Products and services are being released almost every day keeping in mind both the economic and health well-being of customers, and these products/services are adapting AI in most of their offerings.”

How has the demand for data scientists and their skillsets changed since Covid19, and why is the data scientist role still crucial?

“I honestly believe that it is not the skillsets in Data Science that need to change but how we apply them. So, the things that have changed are the problems that we should be looking at. The Data Scientist role is still crucial because only after a careful look at Data will we recognise what problems to focus on. Once we recognise the issues, Data Science will again help us provide reasonable solutions to these problems keeping in mind both the business’s Financial and People aspects.”

Alex Bernal, CMT, CFTe, MSC, Msc Obsidian Quantitative, President at Obsidian Quantitative

How do you think Covid19 has affected businesses adaption of data analytics and AI? Has the adaption been hurried or delayed?

“To be honest it really has just stalled companies from pursuing new projects as they are mostly in distress from Covid and at least in our pipeline have delayed starting new AI project until they get more government assistance or until the economy is clearly re opening. So, mostly delayed because of budgetary issues.”

How has the demand for data scientists and their skillsets changed since Covid19 and why is the data scientist role still crucial?

“Probably not much, skillsets evolve as data evolves and technology changes overtime.”

Tarek Amr, Machine Learning Engineer at TicketSwap, Author of ‘Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python’

How do you think Covid19 has affected businesses’ adaption of data science/AI? Has the adaption been hurried or delayed?

“It’s hard for me to speculate. I’d ask websites like glassdoor and LinkedIn if they have trends for job postings with data scientist titles or ml or similar. I can only guess there’s a decline in demand for jobs in general across the board. Same for spending on data infrastructure and platforms. Based on this, I would assume businesses are cautious to react.”

How has the demand for data scientists and their skillsets changed since Covid19, and why is the data scientist role still crucial?

“I assume businesses will realise the need for automation. The emerge of remote work, thrive of e-commerce, delivery and all related trends will push more for automation, ie machine learning. Also the need to reduce costs and having leaner workforce will push data science more front and centre.

In a nutshell, businesses see the need for data science, but are cautious to react till after the recession. Also waiting for the new business trends to shape their response.”


Wanna become a data scientist within 3 months, and get a job? Then you need to check this out !