What does it take to be a great data scientist?

The need to handle Big Data brought us closer to the realm of data science. The talk of the town now, data scientists are highly in demand in today’s job market. A lucrative career option for many, it is essential to excel in this field to acquire an irreplaceable position. But what does it really take to be a great data scientist?

Curious as you may be, we have listed a few must-haves, required to enhance your skills. These will make you conspicuous and help you stand out from the crowd.

1. Domain Knowledge

To begin working with data sets, it is essential for a data scientist to have a sound knowledge of the domain they are working in. They must have an eye for detail to understand the given business problem. This is vital in order to choose an appropriate data science model which in-turn gives better solutions. Moreover, a data scientist must possess good communication skills to be able to document his/her knowledge. This will allow them to simplify their explanations and make it comprehensible. They should also have the ability to comprehend research work and apply the same in practice.

2. Analytical Mindset

An analytical mindset requires an individual to have a thorough knowledge of his/her subject. Relying on facts and information and not jumping to conclusions is what analytical thinkers are composed of. An analytical bent of mind enables data scientists to picture solutions better. This essentially requires them to be proficient in machine learning algorithms and statistics. Being comfortable with handling large data sets and an expert in R and Python shifts the ball in their court. Most data scientists spend maximum time in making data fit to run machine learning algorithms on them. Data being the Jerry to data scientists aka Tom, they must be habitual of working with volume and variety to manipulate the former.

3. Statistical Knowledge and Programming Skills

A great data scientist boasts of exceptional skills in programming. The key to their lock, data scientists must be deft in machine learning algorithms to unlock the world of data. They must have a sound knowledge of mathematics, typically linear algebra, calculus, probability and statistics amongst the rest. In addition, hands-on expertise in programming languages like Python and R is a primary requisite. An understanding of the libraries such as NumPy, pandas, Matplotlib, SciPy and R is essential too, apart from a brief knowledge of machine learning and deep learning.

4. Problem-Solving

Where it is important to be technically sound in programming and the latest tools, data scientists are incomplete without an aptitude for problem-solving. The more they work on data, the better they get at solving problems efficiently. This is why employers value individuals with hands-on experience. So, in case you want to be “the data scientist” recruiters are looking for, solve as many problems as you can and ace your chances. Internships, competitions or problems solved for leisure can help you add the required spark.

5. The art of Data Storytelling

After having drawn subsequent conclusions from the data provided to them, data scientists must be acquainted with the art of laying their results out in a comprehensible fashion. The complex data structures must be aligned in a manner which makes the picture clear to a wider audience. The result of their data often sets the stage for crucial decisions. So, it is essential for the members of the company to understand what the conclusions speak of.

Data scientists belong to the lot of practical species, who are in love with data. Listing the essentials, we have mentioned the key points required to instill the zing within your system. To be the chosen one, you must hold these points in regard and work on your skills accordingly.

What’s holding you back? Get up and get going! Earn the fame you’re meant for.