Career in Data Science: A Guide for Aspirants

The questions most ask me as a manager of Data Science is what skills one needs to become a successful Data-Scientist. Being in profession of analytics I come across three types of aspirants first, who have experience in analytics; second who have non analytics experience and third who have no experience.

Data science career aspirants can aspire for either of the two main approaches based on current industry. One which involves the data scientist to work on data engineering problems whereas the other involves working with specific or custom analytical solutions. For example, developing a solution which involves combining data from various sources to produce specific metrics for the business objectives applicable across clients (or generic solutions) whereas for custom solutions it may be required to develop models which are specific to one task or objective specific to a business problem.

Once he/she makes a career choice then you must start to acquire skills. If you are someone who has been working in analytics, then the road forward is much easier you must work towards acquiring Machine learning and Analytical programming skills would suffice; and if you are well versed with analytical reporting then too the road ahead is easier. However, you might need to look for a data analyst or senior data analyst roles.

Secondly, for people who have no analytical experience like a software developer or Software tester then the skills to work on would be Database programming, Machine learning and problem solving. However, my suggestion would be to look for a Data Analyst role if you have less than 5–7 years of experience or try to find a role as Senior Data Analyst which require you to be good at SQL/MYSQL and visualizations.

Thirdly, you have no experience try to find a job as data analyst or data engineer which needs database programming skills and would enable you to explore data analytically.

The one skill no matter you have experience or not you need is basic understanding of probability and statistics as this skill is a must if you want to be an expert in data science. In conclusion you need to target skills and focus on specific career goals with long term objectives and any career aspiration must be driven by motivation for learning and rigor.