Data Scientists Roles and Responsibilities

Data Scientists: Data scientists are data analytics experts who discover trends and patterns of data by using their skills like industry knowledge, contextual understanding etc.

“The goal is to turn data into information, and information into insight.”— Carly Fiorina

Data scientists are one of the most highly paid jobs and most demanding careers of today’s time. It is a profession in which a large amount of data is collected, analysed and interpreted. In simple terms, a data scientist’s job is to transform unstructured raw data into meaningful outcomes, so that problems can be solved and optimal organizational decisions can be taken.

In business, data scientists work is to mine big data into information which can be used to predict either customer behaviour and identify new opportunities to enhance growth of an organization. To become data scientists, necessary skills are required which you can get by studying data science. The demand for data science skills has grown significantly with passage of time and increasing data day-by-day.

Roles and Responsibilities of Data Scientists

·      Data scientists manage and structure big data from distant sources. These data magicians are adjustable, to say the least, they create data- driven decision- making frequently by transforming data by using various models or prototypes from trends or patterns.

·      Elementary responsibilities include analysing largedata sets of quantitative and qualitative data.

·      Collecting data and identifying its sources.

·      Analyse a large amount of structured and unstructured data

·      Creating solutions and strategies that focus on business challenges

·      Association of different algorithms to discover trends and patterns of data

·      Representation of information through various data visualization techniques and tools

·      Innovating data strategies by exploring more technologies and tools to create

·      Updating with the latest tools, trends, and technologies to progress in efficiency and performance

·      Creating analytical solutions from collected data for presentation

·      Helping in building data engineering channels

·      Building data-driven solutions for product building team.

·      Team up with members and leaders to project data strategies

·      Assisting team members of Business intelligence developers, web developers, data analysts and business analysts in their projects whenever required.

·      Helping in reducing cost and effort estimation by working with the sales and pre-sales.

·      Designing analytical solutions for business by using machine learning, algorithms, statistics tools etc.

·      Implementing and monitoring data channels and conducting information sharing sessions to the team for operative usage of data for making optimal decisions.

Roles and responsibilities of data scientists vary from organization to organization, depending on their strategies, models etc.

 

Skills Required to Become Data Scientists

To become data scientists, here are following skills required:

1.      Good knowledge of Mathematics and Statistics: Any data scientist should possess a strong foundation of mathematics and statistics, in order to make decisions.

2.      Analytical Skills: The main job of a data scientist is to analyse data and convert it into meaningful results. So, it is one of the prime skills which every data scientist should acquire to gather new insights from chaos of data.

3.      Knowledge of Programming Language: To create practical applications, data scientists need to have strong programming language knowledge. One should possess at least knowledge of any one programming language like C, C++, Java, R, Python etc. to become good data scientists.

4.      Good Communication: Data cannot be communicated if it's raw, it needs to be displayed in presentable form, so that everybody can understand, and so, data scientists should have good communication skills.  As communication can make a big difference in the conclusion of tasks.

5.      Business Acumen: Data can be effective if it is meaningful to employer and decision maker, for which business acumen is required. Data scientists should understand the key of an organization's goals and other important objectives for creating useful solutions.

6.      Data Visualization and Data Manipulation: To provide recommendations, data scientists should present data user friendly. So, presenting data in pictorial form will help in achieving this aim, for which knowledge of data visualization and data manipulation is required.

7.      Fond of Dealing with Data: As data scientist’s deal with data throughout their life, which becomes sometimes dull. So, data scientists should enjoy dealing and handling data.

How to Become Data Scientists?

“The best way to learn data science is to do data science.”— ChaninNantasenamat

There are plethora of sources available on the internet through which you can gain skills and knowledge required to become data scientists. You can take help from various YouTube videos, books, online courses, offline classes etc. to learn data science.

As, due to the pandemic it has become a little difficult for many students to enrol for offline classes but due to the internet it has become easy for all to upgrade themselves. So, some of the best online courses like Coursera, Upgrad, Udemy, Learnbay, Scaler etc. through which you can learn data science and can attain all essential skills required to become data scientists. Learnbay is one of the best institutes of data science online courses in which you can specialize in multiple domains like HR, finance, marketing, banking etc. Even if you don’t belong to the technical world, still you can learn data science from scratch and can master it, as in Learnbay non-technical students get special assistance.

Although other institutes also provide best training but will suggest for all working professionals from any stream to go with Learnbay whereas if you are fresher you can think of Coursera and Udemy courses. All institutes offer the best education platform but individuals have different learning capabilities and requirements. So, choose as per your requirement, whichever is suitable or best for you to make you good data scientists.

 

“We have to learn to interrogate our data collection process, not just our algorithms.” — Cathy O’Neil