The demand for data scientists is increasing, as more and more companies are looking to hire data scientists with the hope that they will create magic by leveraging data. With rising expectations, data scientists are under immense pressure. Managing the expectations is a huge challenge for data scientists who have recently onboarded.
Within no time, data scientists are submerged into the ocean of data collected by the firm over the years, and just trying to understand the data consumes a huge amount of time, even several months. Many times, data scientists end up becoming librarians of data, and just focus on building data governance and metadata management solutions, without delivering any real value to the business.
Many educational institutes train data scientists mainly on the technical aspects, completely ignoring the practical aspects of the profession. While the technical skills are essential for the job, the real challenge for a data scientist is to master the art of identifying the business problems and delivering business value.
Identifying business problems is a huge challenge. If you ask the business, they would say everything is perfect, as they are used to doing things in a certain way. However, with the technical skills and the access to a variety of raw data within the organization, data scientists are uniquely positioned to identify creative ways of achieving business value.
A data scientist should choose a specific business domain – like fintech, healthcare, manufacturing etc, and should have a focus in a specific area, like marketing, sales, operations etc, to be able to identify opportunities to innovate. Data scientists should be closely networked with the business teams working on the ground, to be able to ask the right questions, and explore the right data.
A data scientist is an agent of change and hence should understand the dynamics within the organization. To be able to effectively implement the recommendations, organizations should have the necessary governance mechanism, facilitated by the chief data officer, for incubating new projects and associated change management initiatives.