Wed, Nov 30, 2022
Data Scientist Job Description – Roles and Responsibilities

Data Scientist Job Description

Data Scientists are those people who have the technical skills to solve complicated problems and help businesses grow. This job position is popular amongst candidates because of great future prospects. The average salary of a Data Scientist happens to be $128,750.

Responsibilities of a Data Scientist

  • Responsible for processing the integrity of data used for analysis.
  • A Data Scientist must be aware of Data Mining.
  • Responsible to perform Ad-hoc and present the results in a perfect manner.
  • Responsible for creating automated anomaly detection systems.
  • Responsible for cleansing the integrity of data.
  • Responsible for selecting features and optimizing classifiers using machine learning techniques.

Qualifications

  • Experience with common data science toolkits
  • Great communication skills
  • Experience with data visualization tools
  • Experience with NoSQL databases
  • Should have a data-oriented personality
  • Should have good scripting and programming skills

To grab this wonderful job of a Data Scientist, you’d be required to inculcate the right data scientist skills and they are:

Technical Skills

Education

Data Scientists are known to have a strong educational background as they are required to develop the depth of knowledge in order to qualify for that position. You can also earn a Bachelor’s degree in Physical Sciences, Social Sciences, Computer Science and Statistics. Out of these, the most common fields are Mathematics and Statistics and then comes to Engineering and Computer Science. If you have a degree in any of these courses, you will be eligible to work as a Data Scientist as you will have the necessary skills to analyze and process big data.

People do not stop after getting a bachelor’s degree. The study further on to have a Master’s degree and a Ph.D. degree. Some people also go for online training to learn new skills like Big Data querying and Hadoop which will help a lot.

R Programming

Usage of analytical tools like R programming are essential and are specifically designed for data science needs. Using this language, you’d be able to solve any problem you encounter in data science. This language is specifically designed for Data Scientists’ usage.

It isn’t an easy language to learn but you will find various resources on the internet which will provide proper training to learn this language.

Hadoop Platform

Although it isn’t mandatory for you to be aware of it, it will definitely add to your CV and give you an edge over others. Having experience with Hive or Pig will also be a strong point.

There will be situations where the volume of data be exceeded by the memory of your system or you may want to send data to different servers. Apart from this, you can also use the Hadoop platform for data filtration, data exploration, data sampling, and summarization.

Machine Learning and AI

In order to stand out amongst other Data Scientists, it will be great if you become proficient in Machine Learning techniques. The machine learning techniques such as logistic regression, decision trees, etc. help to solve different data science problems. Now, since Data Science involves working with large amounts of data sets, it would be extremely beneficial to know Machine Learning and Al.

Apache Spark

Apache Spark has made its place amongst the most popular big data technology worldwide. Its computation network is similar to that of Hadoop. The only area where there is a difference is that of Speed. Spark happens to be faster than Hadoop. The algorithm of Data Science is quite complicated and so Apache is designed in such a way that it is able to run faster. It helps in distributing data processing when you are dealing with a big amount of data. It also helps Data scientists to deal with complicated structures.

The main advantages that Apache provides are speed and the platform that it provides which makes carrying out data science projects easy.

Python Coding

The most common language that you will find is Python Coding. In fact, in most of the Data Analysis roles, there is a requirement of knowledge about Python coding. As Python coding is versatile, you can use Python Coding for almost all the steps involved in Data Science developments. It also allows you to create datasets which can be found on Google.

SQL Database Coding

Even though there are other popular and most used coding languages like Hadoop, Python or NoSql, SQL Database Coding is still an important skill that recruiters want their candidates to have. In SQL coding, you are required to use commands such as add, delete, truncate, or extract data from a database. Command over this language helps you carry out analytical functions and transform data structures. Having knowledge about SQL definitely boosts up your profile as a data scientist.

Data Visualization

The business world is known to produce a vast amount of data frequently. Now, this data needs to be interpreted. This can be done by translating the data into an understandable format. There are various data visualization tools that are used for this purpose and they are Matplottlib, d3.js, ggplot, and Tableau. Data visualization gives the opportunity to the organizations to work with data directly.


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Non-Technical Skills

The non-technical skills required in a person who sees himself as a Data Scientist are as follows:

Communication Skills  

Companies generally look for candidates with excellent communication skills so that these candidates help while communicating technical findings that need to be translated to the non-technical team. Communicating about the data related things won’t be easy if they are not translated. It would be better to convey it in the form of a story. It is known as data storytelling. This will make things easier to understand. Most of the business owners are not interested in what Data Scientists do and find, they are actually more interested in the way you use your communication skills to impact their business positively.

Business Insight

A Data Scientist must have a solid understanding of how the industry works. He/She must be prepared to solve the problems that the company might have to face. In addition to that, you must also be skilled enough so that you are able to find new ways to grow the business. For all these reasons, you are required to have a basic business acumen so that you prove to be an asset for the company.

Team Work

A Data Scientist is supposed to work with a lot of people in order to carry out different kinds of projects. So, the quality of working in a team must be there in the Data Scientist. To allow different roles to different people and to make things come together, a Data Scientist is required to have the ability to work in a team and fulfill all the requirements to run the business appropriately.

Final Words

We have provided you with the guidelines that you can follow to ace the job of a Data Scientist. Work on all areas because recruiters are looking out for such candidates. You wouldn’t want to miss out on an opportunity just because you forget to work on a few of the points.

We wish you all the best for your future endeavors.

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