Who is a Data Scientist?

The demand for professional data scientists is increasing at a high rate in the 21 century due to the emergence of complex problems that only this new breed of intellectuals can solve. While they are well-educated individuals, the experts are valued highly due to their exceptional ability to explore problems and solve them. Data scientists are computer specialists, mathematicians, and statisticians who rely on their expertise, social science, and experience to determine trends accurately and manage data.

What are the Duties of Data Scientists?

Data scientists do not have definite job descriptions. But here are some of the tasks that most of them are doing:

Collecting vast amounts of usable data and mining useful information from it
Using data-driven techniques to solve business-related problems
Working with Python, R, SAS, and other vital programming languages
Working closely with It and business departments to help them generate the required data
Finding out the best way to handle missing data by performing exploratory data analysis
Recommend better ways to improve the existing business structures and strategies

How to Become a Data Scientist?

Enroll for an undergraduate degree

You can become an entry-level data scientist if you have a minimum of a bachelor’s degree in computer science, statistics, data science, or mathematics. Education is one of the essential qualifications. 88% of these experts have a least a master’s degree. Also, at least 46% have PhDs. So, once you earn your bachelor’s degree, you need to continue pursuing working hard academically to increase your chances of success.

Acquire technical skills

If you are a holder of a bachelor’s degree in a different field, you need to pursue short courses that can equip you with the technical skills required for the job. These skills include the following:

Programming
Research
Cloud Tools
Data warehousing and structures
Machine Learning Techniques
Risk analysis
Data Visualization and Reporting
Big Data Platforms
Software Engineering Skills
Statistical analysis and Math
Software Engineering Skills
Data Mining, Cleaning, and Munging

Acquire non-technical skills

The technical skills above are critical for the success of any data analyst. But, many people make the mistake of ignoring these non-technical skills and fail to realize their goals.

Intellectual curiosity

Albert Einstein asserted that he had no special talent but was only passionately curious. Since data scientists spend approximately 80% of their time collecting and preparing data, one of the skills you must have is a strong desire to acquire more knowledge. Through this, you are highly likely to acquire more technical skills.

Business acumen

A successful data scientist must fully understand the industry they are working in and its impact on the operations.

Effective communication

Companies want experts who are not only intelligent but also have the ability to translate their technical findings to the marketing or sales department and other non-technical teams. Effective data scientists can pay close attention to the value that is embedded in the data.

Conclusion

If you want to be a professional data scientist, you can use these tips to enhance your ability to use contextual understanding, industry knowledge, and skepticisms to develop novel business solutions.

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