What is data science – What Does a Data Scientist Do?
A Data Scientist is a person who should have multiple skills and has to play multiple roles in his day to day work.
The main aim of the Data Scientists is to analyze the Big Data for extracting the meaning out of it for their organization.
To achieve this, they need to perform various activities such as sometimes they have to work as a mathematician, sometimes as an analyst, sometimes as a computer scientist and much more.
Being a highly paid career and extremely high in demand, the term “Data Scientist” keeps buzzing around us.
But, along with learning the different skills required for data science, you need to have proper knowledge about how those skills are applied to the problems in the real-world scenario.
In this DataFlair Data Science tutorial, we will explore the various aspects related to What does a Data Scientist do in his daily life?
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What does a Data Scientist do – Responsibilities of a Data Scientist
Let us now see various roles and responsibilities of a data scientist:
Data Scientists sometimes need to play the role of a Manager for supporting the planning and execution of various Data Science projects of the Industry.
They coordinate the various tasks that have to be completed by their team for an enormous data project.
Tasks may include researching and creating effective methods to gather data, analyzing information, and recommending solutions to a business.
Data Scientist needs to manage various tasks like the collection of data for the organization, selection of the methods to be applied, etc.
He also needs to ensure team effectiveness, that is, effective work from other members of the team.
Data Scientists play a major role in data analytics.
Analysts consider creating methods to capture, process, and organize data to uncover actionable insights for current problems, and establishing the simplest thanks to present this data.
The Data Scientist builds the best fit models for solving various data analytics problems.
The Data Scientist tries to predict customer behavior for finding suitable data visualization techniques.
They also perform data mining and detailed analysis of very large sets of data related to the organizational strategies.
3. Designing Strategies
The Data Scientist plays a major role in designing new strategies for the organization by understanding the consumers’ trends and behaviors.
It includes areas like overall data science objectives and strategic choices, regulatory strategies, data need, competences and skillsets, data architecture, also as the way to measure the result .
The data scientists perform various activities like the cleaning of data, application of statistical techniques, data analysis, etc. for extracting meaningful insights.
These insights might help the organization in improving its business strategies.
The role of Data Scientist also involves collaborating with many people like the senior Data Scientists, stakeholders, etc.
This is for solving their problems and communicating their findings for improving the accuracy of the results.
For effective collaboration, a Data Scientist must have good visualization skills so that the audience from a non-technical background can also understand what he is trying to convey.
He needs to work with several other teams like data analytics team, data warehousing team, data engineers, business analytics team, etc. for solving various business-related problems.
5. Other duties
Data Scientists also need to fulfill the various duties assigned by the seniors such as Senior Data Scientist, Chief Data Officers, etc. of the department.
Common tasks that a Data Scientist needs to perform
- Asking the appropriate questions for discovering the problems that might benefit the organization.
- Collecting large amounts of data related to the problem from all forms of discrete sources.
- Performing the cleaning process of the datasets for separating the data which is relevant to your problem statement for better accuracy of the results.
- Detailed analysis of the processed data.
- Selecting the most optimal models and algorithms for the problem according to the requirements of the data.
- Identifying the various trends and patterns existing in the data.
- Evaluation and optimization of the results.
- Presenting the results and other findings to the stakeholders.
- Modifying the results based on the feedback received.
Prerequisites for becoming a Data Scientist
Let us now explore the prerequisites to become a data scientist:
- Having one or more degrees in a field related to Data Science such as Computer Science, Mathematics, Statistics, etc.
- Interest in discovering and solving problems creatively.
- Always being ready for grabbing new opportunities and for learning new skills.
- Knowledge of the programming languages commonly used for doing Data Science such as R, Python, SQL, etc.
- Experience in implementing the different skills required.
- Understanding of some popular machine learning algorithms like Decision trees, KNN, etc. and their implementation.
- Good communication skills for effectively communicating with the stakeholders and other team members.
Data Scientists Job Roles
It has been observed that a large number of people confuse Data Scientists with some other roles related to data such as Data Engineer, Data Analyst, etc.
Let us understand how these job titles differ in their roles and responsibilities.
1. Data Scientists
The main role of Data Scientists is to apply various concepts of math and statistics to the data for identifying the relationships, trends, etc. in the data for designing appropriate models .
This is for solving the problems in the best possible way and make some important predictions.
A Data Scientist must have the ability to ask the right questions for identifying different problems.
They should also discover how they are related to the business problems that your organization is facing and find an effective solution.
This helps the organization to make some important data-driven business decisions accordingly.
Along with the other technical skills, a Data Scientist must have very fine communication skills for telling a story with the data while revealing the findings.
The most basic skills required for the role of Data Scientist are Statistics, Math, and Programming.
2. Data Engineer
Data Engineers have a very important role to play in today’s world where ‘Big Data’ holds huge importance.
Mathematics and Statistics do not hold that much importance when it comes to Data Engineers.
They need to focus more on collecting, processing and storing the data.
The data collected from discrete sources for solving various data science problems needs to be converted into such a form that ease the process of analysis, modeling, etc.
This is where Data Engineers have an important role to play. Data Engineers apply various software engineering and coding skills to deal with large data sets.
Data Engineers deal with many responsibilities related to data such as storage, reliability, durability, backup, cleaning, availability, etc.
Along with other programming skills, Data Engineers should also have a knowledge of languages like SQL, NoSQL, etc. which are related to the management of the database.
3. Data Analyst
Data Analyst is also an important role related to Data Science.
The roles and responsibilities of a Data Scientist and a Data Analyst are similar to some extent.
But, the Data Analysts are not much involved in programming, statistics, machine learning algorithms, and some other skills required for Data Scientists.
They deal mainly with the analysis and visualization of the data.
Various tools used by Data Analysts are SAS, Qlikview, Tableau, Excel, etc. They sometimes also perform tasks related to data mining and modeling.
There is another role that is closely related to Data Analyst, that is, Business Analyst.
But the only difference is that they apply the data analytics to the problems related to business for making effective business decisions.
Finally in this tutorial, we have seen the various roles and responsibilities of a Data Scientist.
We also walked through the prerequisites for Data Scientist and some of the other job titles related to the field of Data Science.