“Can we get your name and mobile number please?” This is a question that we are often asked while making a business transaction. While it is not a difficult question, it invades our privacy. This basic information can provide data to an organisation around our preferences, experiences, likes and dislikes and trend of buying a product, etc. Somewhat similar to the concerns around what Facebook has faced over several lawsuits for many years.

Despite a few negatives, the field of data-science has many positives, for instance, a healthcare firm can use data-science to detect anything from breast cancer to depression. Not just healthcare, data-science is used in varied sectors and has become one of the booming career options.

Data has always existed but organisations, until a decade ago didn’t use this field to gain insights and make informed decisions. Moreover, data analysis has been a field technically restricted to the traditional researchers. But today, it is one of the growing fields with an average salary of $1,00,000 in the US.

All technology driven organisations are using data science to create personalised experiences for their customers. This improves customer engagement, loyalty and retention. For instance, Netflix uses data science to personalise its content recommendations for users, track user engagement and retention, which helps it make informed decisions about which shows to produce and how to market them.

Career opportunities

Data science can be used in various fields, such as business, healthcare, finance, and government and a person equipped for a career in data science could have various roles suitable for them. It could be as a Data Analyst – an entry-level data science expert trying to run an existing model using the available data and make interpretable outputs available in various forms.

As one gains more experience in the industry one could become a Data Scientist – engaged in creating new models. At this level, one would be expected to prepare their own machine learning or deep learning models, which could be used for predictions by analysts. A data science expert is expected to give a deeper understanding of the business problems with the help of domain knowledge and even make strategies. This would also require a deeper understanding of the data-generating process as well as methodologies for effectively describing the data. They could further go on to become Senior Data Scientists or become Directors of Analytics in an organisation.

Another path a data science professional could pursue is that of a Data Engineer. This path would be more suitable for someone with a background in technology – familiarity with cloud, query, database and the applications used for these. Here, one would be expected to maintain a database and design analytics for multiple platforms. Data Architect would be an expert responsible for creating a custom solution for data management in line with the demands and strategies of companies.

Business Analyst is another career option for people with a background in economics or business. In this role, the person would be responsible for creating analysis using data like a data analyst, but additionally responsible for creating business insights. Domain expertise would be a desired additional qualification, which would be helpful in diving deep into the business problem and giving an executable solution. One could aspire to go to a higher profile as a Business Intelligence (BI) Developer, where the role would expand to developing a tool or integrating existing tools with more functions to enhance the existing business analytics.

Another career choice that also involves client coordination is of a Data Consultant, who is required to understand the data science techniques, explain and interpret insights. A person having good interpersonal skills along with domain expertise would excel in this role.

Problem Solvers

There is never a dull moment in the career path of a data-scientist who is known to be a data problem-solver for an organisation. If a hospital is having trouble deciding where to open its new branch, then a data-scientist can analyse demographic data, population trends, healthcare needs and identify gaps in care, and develop a strategic plan for meeting the needs of the community. Besides this, a data scientist could forecast patient volumes, predict staffing needs, and estimate resource utilisation for the new branch. This could help the hospital optimise its operations and ensure that it has the resources necessary to provide high-quality care.

Overall, data science can provide valuable insights and intelligence to help a hospital make informed decisions, optimise operations, and ensure that it is providing high-quality care to its patients. By leveraging the power of data, a hospital or any other organisation can increase its chances of success in opening a new branch and fulfilling its mission of providing excellent services to its community. A specialised knowledge in a core domain of data science would keep one well prepared for fast growth in one career as a data science professional.

(Dr Rohit M is an Assistant Professor of Economics at Shiv Nadar University, Chennai.)