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Table of contents
1.
Introduction
2.
8 Must-Have skills for Data Scientist
2.1.
1. Math and Statistics
2.2.
2. Analytics and Modeling
2.3.
3. Machine learning Methods
2.4.
4. Programming
2.5.
5. Data Visualization
2.6.
6. Intellectual Curiosity
2.7.
7. Communication
2.8.
8. Business Acumen
Last Updated: Mar 27, 2024

Skills required to become a Data Scientist

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Ashwin Goyal
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18 Jun, 2024 @ 01:30 PM

Introduction

By this time, you must have an idea about what is a Data Scientist, guessing that you must have gone through our last blog, The Hottest job in town- Data Scientist! And, if you haven’t, then what are you doing Dude… 

Because you know Data Scientist has been voted the “sexiest job of the 21st century”, and we want you to have full knowledge about this. 

Anyway, here we are again with the skills you need to become a Data Scientist. You’ll need a much wider swath of skills to succeed at the higher level of your career. Even so, no matter your role, if you wish to become a Data Scientist, you must possess certain skills.

8 Must-Have skills for Data Scientist

1. Math and Statistics

If you scored well in mathematics, then there is no such problem for you. You already have the most significant skill. Any good Data Scientist needs to have a strong foundation built both on Maths and Statistics. 

 Data science professionals are required by any business, especially those who are data-driven, to be capable of analyzing data using different approaches to statistical analysis – including maximum likelihood estimators, distributions, and statistical tests – to assist with recommendations and decisions.

2. Analytics and Modeling

To extract valuable information from an organized data set, a data scientist needs to know analytical tools. The most popular data analytics are SAS, Hadoop, Spark, Hive, PIG, and R. Getting certified as a data scientist can help you gain valuable skills and increase your expertise using these analytical tools.

And you know where to go for a certification in Data Analytics; obviously Coding Ninjas! 

3. Machine learning Methods

Even though you don’t need to be an expert in this field, a certain level of familiarity is expected. There are a number of machine learning tools which can be employed, including decision trees, logistic regression, and more. Potential employers will be seeking employees with these skills.

To become an expert in  Machine Learning, we are there for you with a course built for both Beginners and Experienced learners. 

4. Programming

This is the basic that everyone who wants to be Data Scientist should be fluent in. Almost every employer expects you to be able to program in both Python and R. Object-oriented programming, basic syntax and functions, flow control statements as well as libraries and documentation all fall under this umbrella. 

If you want to brush up on your programming skills and want to get your basic clear, you know where to go for programming certification.

5. Data Visualization

As a Data Scientist, it is imperative that you are able to effectively communicate key messaging and gain buy-in for proposed solutions using data visualization. Any Data Scientist who wants to advance in their career will need to know how to decompose complex data into digestible chunks and how to use visual aids (charts, graphs, and so on) to achieve success.

6. Intellectual Curiosity

Are you an intellectual or a curious kinda, guy/gal? To be a data scientist, you need to join your hands together, which means you need to be an intellectually curious person! It means that you need have a curious mind to solve problems and find solutions — especially ones that require some out-of-the-box thinking. 

The Data Scientist is fueled- by a desire to understand more about what the data is telling them and how to make that information more widely useful.

7. Communication

If you were a backbencher then, there is no problem because we already know you are the talkative one but can you frame your words eloquently? Yes, being talkative or an extrovert is not the same as having good communication skills, but what matters is how efficiently you can communicate.

You have to be master both verbal and written communication. Because in a data science project, after concluding the analysis, the project has to be communicated to others, like sending a report to your boss or coworkers.

8. Business Acumen

The data scientist must have a level of business acumen to effectively make use of their employer’s data. You need to understand the key objectives and goals of the business and how it impacts the work you’re doing. Achieving those goals requires building solutions that are cost-effective, easy to implement, and widely adopted. 

Since these roles require someone who is capable of not only handling the data but also translating and communicating it across the organization, they require someone who can not only handle the data but also communicate it to key stakeholders.

You can also consider our online coding courses such as the Data Science Course to give your career an edge over others.

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