5 Ways To Build A Successful Career In Data Science
To understand how can students build a successful career in data science, let us dive in deeper.
The field of data science is constantly growing and evolving, enabling businesses to arrive upon data-driven decisions. Companies are witnessing an onward trend in utilizing copious amounts of data to gather insights in order to ramp up, modify or refine their business model. This is one of the biggest reasons why data scientists are in demand, despite the pandemic. Businesses operating in different industries and domains are depending upon data science to develop products, create effective marketing campaigns, and conduct market research. Afterall data-driven decision making empowers organizations to make well-informed decisions rather than basing the decisions upon intuition.
Engineering students who want to carve a career out of data science need to be careful about their job profile and the right company that can accelerate their career growth. Taking a plunge from a core engineering role into a data science career might take relevant education and experience. In order to cater to the industry demand, engineering colleges are also enabling students to take up data science courses and specializations.
Data science requires a statistical bent of mind which can be acquired through handling and crunching huge amounts of data and gaining knowledge of the right tools and techniques from the very beginning.
To understand how can students build a successful career in data science, let us dive in deeper:
Select a tool/ language to specialize: It is important for students to understand and have an in-depth end to end knowledge about the topic they want to pursue. For engineering students, a question that might bother is which language or tools they should specialize or get hold of. Machine learning tools are often seen as a stepping stone to learning data science. Some other languages like Java, Python, SQL, R, are some of the significant languages that help to acquire the right skills to analyze data.
Learn practical applications: While institutes and MOOCs (Massive Online Open Courses) will help you to learn the tools and theories, it is important to understand the practical application of data science. This can be done by working on a few open data sets and deriving insights. Another way to look at the practical application is through use cases, where experienced professionals have worked on data sets and the solutions they have provided.
Build your communication skills: Data science is a technical role and the association of communication skills for such job roles might often be undermined. However, students need to work on their communication skills and also be technically profound to bag a data science job offer. Communication skills not only help you to bag an offer but also during your professional career in the data science domain. Since it's a role where insights have to be presented to the leadership, ideas have to be communicated to colleagues, building these skills are really important.
Choose the right role: Data Science is a growing industry and one can find a plethora of job opportunities and different roles. Some of the varied roles include data engineers, data visualization expert, machine learning expert. It is important to choose a role and transition into the right one, with the relevant experience. To understand the demand and the role suitable for an individual, one can talk to people in the industry, join peer groups and follow the right resources.
Become a critical thinker: Data Scientists need to extensively understand, listen and arrive at solutions. One needs to be on top of trending technologies like Machine Learning and Big Data to be able to critically analyse the problems. The demand for data science is the steepest in the IT industry and the job roles need advanced educational qualifications. This can be achieved through pursuing your specialization and also completing online coursework on relevant tools. This will also help to build critical thinking ability in students.
In order to build a successful career in data science, students need to shore up their analytical abilities and also find the right course to pursue at the beginning of their career. With the right education and skill set, students can enjoy a bright career outlook as a data scientist.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house