Sunday - May 27, 2018

Career Paths For A Data Scientist


Career Paths For A Data Scientist

With the emergence of Big data in organizations around the world, data science teams comprising of data scientists and data analysts are becoming gradually critical for organizations. Data science teams work together to derive business benefits from the enormous amount of data generated by the organization. As part of the data science team, a data scientist is able to translate a business problem into a data question, and then apply statistical and mathematical methods to generate a predictive model to solve the data question.

Along with possessing knowledge about the use of algorithms, statistics, and mathematics, data scientists must have practical knowledge of R and Python programming languages.

As an aspiring data scientist, what is the right career path that you can take? This article attempts to address these issues.

Choosing the Right Data Science Career

Data science comprises of different functions and roles including data visualization, machine learning, and data engineering. Is becoming a data scientist the correct role for you? This could depend on your academic profile and your work experience. Gather as much information about each data science function and job role to choose the one that suits you the most.

Choosing the Right Training Course

Once you have decided on the right role, it is important to undergo a professional training course to be certified as a data scientist. With the growing industry demand for data scientists, there are many training courses that claim to equip you with the practical skills for a career as a data scientist. A comprehensive Big data analytics training course from a reputed institute would be the right beginning for an aspiring data scientist. Training courses, which impart practical knowledge of the concepts, would benefit you in the real-world scenario.

Learning Python programming for data science is also essential for data scientist. A web designing course that specializes in teaching Python web development frameworks such as Django, Flask, or CherryPy would not be a suitable fit for learning Python for data science.

Keep Yourself Updated with Industry Trends.

Data science is a constantly evolving industry with new trends and insights, provided by experienced data scientists through technical and information blogs. It is important to keep yourself updated with the latest advancements & practices and follow the right online resources.

Improve your Communication Skills.

As a data scientist, you are not only expected to have technical skills, but also have the ability to communicate your data insights and business ideas effectively to the company’s management team. Learn to communicate your skills effectively while introducing yourself during interviews.

Conclusion

With companies investing their time and money in data science functions, it is important for aspiring data scientists to acquire the right skills that can enable big data analytics for their companies. Hence, choosing the right career path is critical for your development in this growing field.