Data science has been no more a luxury for companies — this COVID-19 pandemic has forced companies to rely on data-driven strategies, and thus made data science a key aspect in running businesses. Not only it is helping countries to assess COVID-related data and trends for its citizens but also supporting industries like manufacturing, retail, and e-commerce to sustain in this pandemic.
And therefore, companies in India and across the world are looking to include more data scientists in their team to analyse information and help leaders make an informed business decision in this crisis. In fact, despite COVID-19, there are many companies in the news, which shared their hiring interest to work on innovative services and gain a competitive edge among their competitors.
However, there has been a significant change in the hiring strategies in the majority of these companies. With cost-cutting being a primary concern for companies, the majority of them are looking to hire data science generalists instead of specialists amid this crisis. In fact, there has been a growing demand for data science generalists since a long time, Gartner called them “citizen data scientists,” who are a jack of all trades — knowing a bit of all the technologies and tools related to data science. Although these generalists aren’t an expert in advanced specialisations within machine learning and deep learning, etc., these generalists are known to create models leveraging predictive analytics as well as a hold on business acumen skills.
In fact, it isn’t easy to be a data science generalist. One has to work on various projects, study several subjects, and work in different domains to be competent in this generalised field.
Apart from cost-cutting, these generalists can also help bridge the talent gap that the majority of companies are facing in this crisis with analytics work, where they are expecting a mix of data science with engineering and application programming knowledge. Madhavi Kaivalya Kandalam, the vice president and chief data scientist of Loylty Rewardz said in an interview with Analytics India Magazine that corporates tend to look for more generalist data scientists.
A Case For Data Science Generalists Amid COVID-19
This COVID crisis has altered many strategies as to how businesses used to work before this pandemic. Similarly, in the case for data scientists, where earlier specialists were highly favoured in the industry over generalists, it has been changed to hiring more generalists at this uncertain time. A significant reason for this is the inability of specialists to go beyond specific domain knowledge. However, in this tormenting time when things are ambiguous for the foreseeable future, there is a massive requirement for generalists who are well-versed with all aspects and are comfortable to steer through unchartered territories of data science to lay the groundwork.
Although a specialist comes with profound knowledge of a particular aspect of data science like NLP and computer vision, a generalist is the one who can actually combine all these together to bring out better business outcomes at a lesser cost. Generalists are capable of communicating insights to business leaders and have skilled knowledge of BI tools like Tableau, SQL, and expertise in algorithm design and optimisation. These skill sets can help companies in their business problems.
Alongside, analysing massive amounts of unstructured data and making APIs and dashboards have been a critical concern for businesses to streamline their processes amid this crisis, and generalist data scientists can help businesses achieve it, without any specialised knowledge.
Even for startups and small businesses, this crisis has brought immense difficulties in creating a core data science team to innovate on new services, and that’s where generalists come a lot handy. These generalists can come on board for lesser salaries than experts and specialists and also enable companies to look at a project with a different perspective, helping them innovate in new areas of data science. Alongside, with companies becoming more data-driven, leaders are looking for professionals with critical thinking capabilities with a wide range of knowledge, which is an important factor in data science generalists.
Encouraging generalists in organisations also enhance the learning curve, as the job roles become more domain and technology agnostic. Alongside, data science generalists can perform diverse functions from the conception of a solution to building a model, and remain flexible in the dynamic environment, which in turn help companies to gain more benefit with less human resources. In fact, if required, when companies mature, they can also turn their generalists to specialists by providing them with necessary training.
Lakshya Sivaramakrishnan, Program Lead at Women Techmakers India, said, having a generalist also positively impacts in terms of the number of tasks that a person can get done. “Like instead of hiring five specialists, I can have two generalists who would help me in actually getting the task done, which isn’t the case with specialists,” said Sivaramakrishnan.
She further said, “If there is something with specialisation in exploratory data analysis, or in model building, they wouldn’t be able to know or understand the entire workflow of the project to make necessary changes, which can easily be done by a generalist who can bring a breadth of knowledge to the table.”
For aspiring data scientists, it is critical to understand that knowing the full picture and understanding the flow of the data science projects is vital for them to actually term themselves data science unicorns. In fact, to create machine learning models, it is necessary for data scientists to understand every aspect of it to make solutions that can actually solve problems. And once aspirants are well-versed in the basics of data science, it’s when they will be able to choose the right specialisation for making a career growth.
Admond Lee Kin Lim, data scientists at Micron Technology and a Medium blog writer, wrote on his blog post that, for starting data scientists it is recommended to be a generalist first, and for that joining a startup could be the best way, where not only they get exposure to work with various team and on several projects, but also get the opportunity to create something from scratch.
In fact, according to Lee, a marker of an ideal data scientist is someone who has strong general knowledge and is capable of bringing in unique specialities complementing his/her organisation.
Also being a specialised data scientist would restrict the growth of the individual as they will have to look out for a change in the same domain. And therefore for fresh graduates having a generalised knowledge would help them widen their prospects in the market. These generalists also have a leg up on specialists in terms of handling the business, as having expertise across different areas of the field will make them a more preferred choice to lead a team of specialists. Consequently, in this crisis, general data scientists will have a better chance to land on jobs than highly paid specialists.
Although specialists bring huge benefits to companies, this COVID pandemic has entirely altered the scenario of the data science landscape. Bearing the costs and sustenance in mind, companies are now looking to get benefit in each of their hirings, and therefore, could rely on generalists to get the maximum benefits. However, for aspiring data scientists, it has been imperative to become a generalist first before actually specialising in a specific domain, which will not only help them choose the right career path but will also help them become a better expert with relevant knowledge across the field.