A certification in Data Science opens up multiple avenues for career transitioning and growth. One must understand that this role is not restricted to only hands-on statistical model building but also to engaging in consultative work to improvise the data strategy and overall use of data for problem-solving. Let us explore a few career options and understand the pros and cons that one might face in the long run.

Data Scientist : Leverages statistical tools and algorithms to manage data and encourage data driven decision making.

Big Data Manager: Manages end to end data pipeline and data strategy.

Data consultant : Advises clients on the ways to solve complex problems using a data driven approach.

Data Analyst : Acts as a bridge between the technical and the functional teams to bring a solution or product to life.

ML Lead: Leverages both Machine Learning and Data science to manage and solve use cases with a data driven approach.

AI consultant: Understands and works on integrating Data based problem solving with other AI based solutions. This is usually done by building an AI platform to integrate multiple solutions.

Opportunities in the data science domain increases with your level of expertise and exposure. The industry is witnessing continued demand from professionals who can build an organization-wide AI platform that can set up the data platform and leverage it to solve multiple use cases. Professionals can take advantage of multiple certifications and programs available to learn how data science is used to problem solving across domains and industries.