From Classroom to Business: How can Data Scientists make a Seamless Transition

Data science is a booming industry, even with the COVID-19 pandemic rampant! Data scientists have the option to apply their skills in any industry out there, due to the interdisciplinarity of the field. The pandemic has massively affected nearly all industries but the demand for data scientists especially in the healthcare sector has increased manifold. This, in turn, means a rise in the number of students looking for Data Science courses, as the job market henceforth will be potentially dominated by Data Science. 

Students who are looking to pursue data science after an undergraduate degree should keep in mind to look out for courses that offer in-depth knowledge in information systems management, machine learning, econometrics, applied modelling, proficiency in R, Python, Tableau etc. Interestingly, ISBF offers a postgraduate diploma course in Data Science, which encompasses all of the above. This 1-year long course is academically designed and assessed by the London School of Economics; upon graduating, students receive a diploma from the University of London. Academic direction from LSE means that the course is rigorous and has been created by top-notch experts in the field of data science. This diploma offers a world-class education to students who are truly interested in making a mark in this field. 

Apart from gaining relevant knowledge from an advanced curriculum, students and potential data scientists must also possess some extra skills that provide them with an edge. These added skills can help data scientists make a seamless transition from the classroom to working in the business of your choice. The lockdown has given students an opportunity to upskill and potentially prepare themselves in a data science role. Below are some additional skills that one can work on to make a smooth transition from a learning environment to the application:

Business Acumen/Choosing a Specialisation

To implement technical knowledge gained from studying a data science course, one must possess a solid understanding of the industry they want to work in. It is advised that students opt for a data science course as an added specialisation in their areas of interest. Additionally, one must also be aware of the industry trends, to keep abreast of the problems they are facing and how one can tackle them using data analytics. 

Communication Skills

Companies who actively hire data scientists look for individuals with excellent communication skills; this means that one must be able to translate all technical findings to non-technical teams in an organisation. They should be able to do so clearly and fluently. Usually, such data is actively helpful for marketing and sales teams, a data scientist must be able to arm such teams with concise information from the data. No business or team wants to know how you achieved it, all they want to understand is how the information is useful and what the findings are.

Networking and Curiosity

Networking and conferences are great ways to keep up with the dynamic world of data science. Attending AI (Artificial Intelligence) conferences can help one gain a better understanding of what the future of AI and data analytics is, what are current shortcomings that one has to address, areas that need improvement, a new development in technology etc. Such developments make a huge impact on the data scientists of the world and they are important to keep track of. Another perk of attending such conferences is the fact that they can help you find a great mentor who is willing to guide you through the professional curve. 

These are some of the additional skills a data scientist should possess. However, they are not all, some of the others include basic skills like teamwork, problem-solving, taking initiative/ proactiveness, self-management etc. A combination of these skills can pave the way to a brighter future in data science.