The Best Path to Becoming a Data Scientist


The newfound passion for data science in the present computing world isn’t baseless. Rated as the top job on offer by Harvard Business Review along with lucrative paychecks, the lacunae in the current skills of experts compared to the industry standard skill-set necessary for the position of a data scientist means there is very much already that comes with learning data science.
In such a setting, what gives you a competitive edge? Here are a few steps to follow on your path to becoming a data scientist!

1. Develop Skills in Statistics, Mathematics, and ML

A data scientist is someone who is better at mathematics and statistics than any software engineer and also better at software engineering than any statistician. You just need to have the right balance of all these, to ensure you’re set up well to develop your data science skills.

2. Learn to Love (Big) Data

Data Scientists have to handle a massive amount of structured and unstructured data on which computations cannot be performed using any single machine. Most of them use big data software such as MapReduce, Spark, or Hadoop to achieve distributed processing. Various online data science bootcamps can really help you to learn big data faster.

3. Gain an Exhaustive Knowledge of Databases

Given the massive amount of data generated almost every minute, most organizations employ database management software like Cassandra or MySQL to store and evaluate data. Good insight into the mechanisms of the DBMS will undoubtedly go a long way in getting your dream job as a data scientist.

4. Learn to Code

You can never be a good data scientist unless you learn the language in which data converse. A well-categorized amount of data might be shouting out its analysis; the writing may be on the board, but you can only understand it if you know the script. Therefore a good data scientist should always be a good coder.

5. Master Data Munging, Visualization, and Reporting

Data munging is the procedure of converting the raw data into a form that is easy to study, evaluate, and visualize. The visualization and presentation of data are an equally essential set of skills on which a data scientist relies heavily when facilitating administrative and managerial decisions using data analysis.

6. Work on Real Projects

Once you have attained the theoretical knowledge of the field, it is all about practice. Search Google for data science projects and invest your time building your own strengths, along with zeroing in on the areas that still need brushing up.

7. Stay Informed With the Data Scientist Community

Follow websites like Data Science 101, KDNuggets, and DataTau to remain in sync with the happenings in the field of data science and gain insight regarding the kinds of job openings presently being offered in the field.

We hope the above steps help you take off on your data scientist ambitions and help you build a successful career in the field.

Location: Bengaluru, Karnataka, India

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