Top Ten Reasons to Distinguish a Good and a Great Data Scientist

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What is data science?

Data science is the process or a method of gathering information from data that can be arranged, collected, and stored at a large scale.  Data science has ample opportunity and every industry gets insights from it to make decisions and work systematically and has multiple real-life applications.  The impact of Data science can be seen in every field around the world and without data science, businesses can miss opportunities and can make flawed decisions, and can never succeed.

Who are Data scientists?

Data science professionals are the ones who understand and explain data to help business organizations and other fields make better decisions. Data science professionals are responsible for collecting the data, analyzing the data, and interpreting it for the organization and companies. Data science professionals are experts of data who uncover solutions and results.

They use computer science, math, and business sense and combine them with statistics and analytics to solve major questions related to data.

What differentiates a great Data Scientist from a good Data Scientist?

It is not surprising that businesses want to hire the best people and always retain them. People with skills and those who assess characteristics and qualities will always be valued more.

There is no shortage of skillful people in Today’s work scenario. Everyone is working on enhancing their knowledge and qualities to compete with one another. But there are major differences between a good and a great Data scientist. The great data scientist will always bring a positive change to the possible.

However, a mediocre one will disrupt the company’s time, money, and resources.

The Major difference which can sum up between great and good data scientists are:

Optimal use of one’s time

Using your time efficiently increases productivity and helps in producing value for the organization faster.

But there are certain rules that are required to be followed.

  1. Follow the 80/20 rule: A great scientist should always follow good models and by following good operational models they can handle multiple projects by spending less time.
  2. Working out of the box may not always work: A great certified senior data scientist is one who relies on traditional methods to extract maximum benefits and save time and resources. Relying on reusable codes, python, and library sources whenever possible can save a company’s resources and money.
  3. Understanding the importance of Excel: Sharing full analysis or even advanced analytics on Excel can help non-tech people to understand data related to marketing, sales, and product. Certified senior data scientists will always understand the importance of Excel and work effectively on it.
 Optimal use of other’s Time
  1. Asset for management: A certified Data Scientist will always understand what management wants and what are the main issues that the management is trying to solve, this reduces a lot of meetings and formalities.
  2. Embracing simplicity in the work: Relying on simplicity is one of the most important skills of certified senior data scientists. Using simple operative models and language whenever possible will make the work more accessible to people and even to non-tech. It also reduces risk and has a positive impact.
  3. The magic of visualization and charts: A great certified senior data scientist always tries to make interpreting data easy. Presenting data through gifs, charts, and animation is worth many presentations, they are easy to produce and understand and don’t even require coding.
Data and model understanding
  1. Acumen to work on missing data: Data science professionals are also required to work on data that may not be present entirely but these unobserved and missing data can help in analyses as they are highly underestimated. Such data generally help in predictions and analyzing future trends.
  2. Understanding the possibility of the model and results: A certified senior data scientist always under- promises but always over-delivers by his performance. Data scientists assess every problem and analyze it to give an efficient solution.
Community feedback
  1. Learning should never stop:

A certified senior data scientist never stops learning to upskill his talent, knowledge, and using the right search engine. Data science professionals can depend on online courses or also can self-learn.

  1. Publish the work for feedback: Feedback gives a clear picture of the work and what improvements can be made to enhance the articles.

There are various platforms where data science professionals can share their work with each other and can improve.

Importance of Data Science Certifications

Data science courses, especially certificate courses, give data science professionals an opportunity to work and develop skills that are required to work in the desired industry.  Senior data scientist certification can enhance their skills and can work on their careers and develop their overall knowledge. There is a lot of significance in certificate courses as it always validates skills in the eyes of employers and recruiting managers. It is demonstrable proof of the value that will be added by a data science professional.

But, a data science certification alone cannot make a professional land a job. It will only add experience and the professional portfolio that is needed to get a job.

An effective certificate course focuses on overall knowledge development and solid technical expertise.

A data science professional should choose the course with utmost care which suits his/her ambitions. There are multiple reputable courses at minimal rates which offer endless possibilities. The duration of the course varies from program to program. It can take a couple of days or even months.

Senior data science certification from premier certification bodies and institutes such as USDSI, Stanford, MIT, North Carolina, etc., can help in the overall transformation of a career and boost overall development.