Data Scientist Job Description & Roles and Responsibilities
A Data Scientist is an expert who looks at complex data sets to gather sensible data and guide navigation. He or she examines information patterns, examples, and connections utilising measurable strategies, AI calculations, and programming skills. A Data Scientist utilises information-driven techniques to tackle issues, assume results, and develop systems in various areas.
Data Scientist Job Description
A Data Scientist is expected to gather, study, and evaluate massive datasets to identify patterns, examples, and bits of knowledge that guide system and business choices. He or she utilises measurable strategies, AI calculations, and programming languages like Python or R to process and work with information. He or she performs tests, makes expected models, and reports or presents discoveries to partners.
A Data Scientist works with cross-functional groups to settle testing issues, smooth out methods, and improve labour and products. The outcome in this position requires areas of strength for scientific capacities, programming skills, and subject mastery even though the ability to work well in a speedy, powerful working environment.
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Data Scientists Roles and Responsibilities
A data scientist is critical in extracting insights from complex datasets to drive informed decision-making. His or her responsibilities include collecting and cleaning data, conducting exploratory analysis, developing predictive models, deploying them into production, and communicating findings to stakeholders. He or she leverages statistical techniques and machine learning algorithms to extract actionable insights that contribute to organisational success and innovation. Some of the key data scientist duties have been given below:
Management: A data scientist performs a small managerial function by helping to build the foundation of futuristic and technical talents within the data and analytics sector. He or she does so to support different planned and ongoing data analytics initiatives in the organisation.
Analytics: A Data Scientist is a representative of a scientific position who develops, applies, and evaluates advanced statistical models and techniques for use in the most challenging business problems. A data scientist creates statistical and economic models for a variety of issues such as projections, classification, clustering, pattern analysis, sampling, simulations, and so on. This is one of the most important data scientist duties that the individual has to carry out.
Strategy/Design: A Data Scientist plays an essential part in the development of creative approaches to comprehend consumer trends and management for the company, as well as approaches to tackle challenging business issues like optimising product fulfilment and total profit.
Cooperation: A data scientist's job is not a solitary one. He or she works in a team with more experienced data scientists to convey results and challenges to pertinent parties in order to improve company performance and decision-making. This is another one of the key data scientist duties.
Knowledge: A Data Scientist takes leadership in investigating various technologies and instruments to generate creative data-driven insights for the company at the fastest possible speed. He or she also takes the initiative to evaluate and apply improved and innovative data science techniques for the company.
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Career Path Progression For Data Scientists
The field of Data Science is continually developing and is relatively young. One has a lot of options in the Data Science industry to place his or her career. Each of these roles has a different set of duties and demands a different set of abilities. Prominent instances of these roles include data scientist, data engineer, data analyst, data science manager and so on.
Junior Data Scientist: It is an entry-level role that is well-suited for fresh graduates or professionals with a minimal experience history in this domain. For example one will do basic data science jobs like deriving insights using data collection from various databases, data mining or analysis; building a predictive or prescriptive model using programming languages such as Python or R, and so on.
Senior Data Scientist: A minimum of four-five years of experience executing Data Science solutions is required for this senior post. One should be able to work with complex or unstructured data, comprehend business challenges and convert them into data solutions. Additionally, he or she would have to spearhead and oversee several data science projects for the companies.
Data Engineer: A data engineer is in charge of creating data infrastructure and handling raw, unformatted data that has faults from machines or people. He or she creates, constructs, and develops ETL pipelines to prepare the data by cleaning and formatting it. He or she uses a variety of big data technologies and refined programming languages to build these data pipelines
Data Science Manager: One must have at least five to ten years of experience implementing different Data Science solutions for this management position. Leading a group of Junior or Senior Data Scientists to oversee and manage the application of data science solutions for a company would be the job in this position.
What are the qualifications required to become a Data Scientist?
To become a Data Scientist, one usually begins with a 10+2 education from a recognised board, followed by a bachelor’s degree in the field of computer science, mathematics, or statistics. Graduates can enter the field directly or pursue a master’s programme for advanced skills.This path equips students for higher-level roles and enable them to contribute in the field of data science.
Bachelor’s Degree Programmes
- BTech CSE
- Bachelor of Computer Application
- BSc(Computer Science)
- BSc(IT)
- Bachelor of Science(Statistics)
- Bachelor of Science(Mathematics)
Master’s Degree Programmes
- Master of Technology(Computer Science and Engineering)
- Master of Computer Applications
- MSc(Computer Science)
- MSc(IT)
Data Scientist Skills
Here are some of the skills that you must possess to become a Data Scientist. We have mentioned below both soft skills and hard skills for becoming a Data Scientist. Some of the soft and hard skills that are required to opt for a career as a Data Scientist are as follows:
Hard Skills :
- Programming
- Data Visualisation
- Machine Learning
- Probability and Statistics
- Mathematics
- Big Data
- Python
- R
- Data Wrangling
Soft Skills:
- Creativity
- Communication
- Time Management
- Adaptability
- Collaboration
- Problem-Solving
Top Recruiters for a Data Scientist
The top employers in India for data scientists include multinational corporations like Accenture and IBM India and IT consulting firms like Tata Consultancy Services, Infosys, and Wipro. E-commerce Giants like Flipkart and Amazon India are actively seeking to expand their data science talent pool. These companies are offering a variety of jobs, depending on how data scientists can transform the market.
- Tata Consultancy Services (TCS)
- Infosys
- Wipro
- Accenture
- Capgemini
- HCL Technologies
- IBM India
- Genpact
- Paytm
Data Scientist Salary in Top Companies
Top Indian firms like Infosys, Tata Consultancy Services, and Wipro pay data scientists well. They also receive high salaries in multinational companies such as IBM and Accenture. Data scientists are also paid well by e-commerce giants like Amazon and Flipkart. However, experience, skills and expertise affect the Data Scientist Salary.
Company | Average Annual Salary |
|---|---|
TCS | Rs. 9.9 Lakhs |
Wipro | Rs. 11.2 Lakhs |
Accenture | Rs. 14.6 Lakhs |
Genpact | Rs. 14.6 Lakhs |
Paytm | Rs. 16.4 Lakhs |
Source: AmbitionBox and Glassdoor
Related:
- Data Scientist Salary in India - Average Salary Packages, Skills, Types
- Data Analyst Salary in India for Fresher & Experienced
Conclusion
Data scientist is essential in today's data-driven environment. He or she can extract useful insights from massive data sets with the use of analytics, machine learning, and problem-solving techniques. The role of a data scientist is crucial in determining how various businesses will develop in the future.
Frequently Asked Questions (FAQs)
A Data Scientist gathers, studies, and evaluates massive datasets to identify patterns, examples, and bits of knowledge that guide system and business choices. He or she utilises measurable strategies, AI calculations, and programming languages like Python or R to process and work with information.
To become a Data Scientist, one usually begins with a 10+2 education from a recognised board, followed by a bachelor’s degree in the field of computer science, mathematics, or statistics. Graduates can enter the field directly or pursue a master’s programme for advanced skills.
The pay range for a data scientist in India is Rs 3.9 Lakhs to Rs 28.0 Lakhs, with an average of Rs 14.4 Lakhs per year.
Yes, it might be challenging to get into a data science degree since it requires a strong foundation in math, statistics, and computer programming. But anybody who puts in the necessary time and effort may get the skills and information needed to succeed in this field.
One might be able to acquire the fundamentals of data science in a year if he or she is committed and has a solid background in maths, statistics, and programming by taking online classes, taking part in projects or competitions, and looking for extra learning tools.
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Questions related to
Hello student,
When comparing NIT Jalandhar and PEC (Punjab Engineering College) for placements, both colleges offer good opportunities, but there are some differences to consider:
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Placement Rate : Both have strong placement rates, but PEC, being an older and more established institute, often attracts more high-profile companies, especially for core branches like CSE, ECE, and Mechanical.
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Average Package : PEC generally offers slightly higher average packages, particularly in branches like CSE and ECE, as it is located in Chandigarh, a corporate hub. NIT Jalandhar, however, also has competitive placements with good packages, especially for CSE.
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Location Advantage : PEC’s location in Chandigarh provides better internship and job opportunities due to proximity to corporate offices and industries compared to Jalandhar.
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Alumni Network : PEC has a longer-established alumni network, which can be beneficial for placements and networking.
Overall,
PEC might have a slight edge in placements
if both colleges offer the same stream. However, both institutions are reputable, so you can expect good placement support at either one.
I hope this answer helps you. If you have more queries then feel free to share your questions with us we will be happy to assist you.
Thank you and wishing you all the best for your bright future.
hello Aspirant ,
The study of Electronics and Communication Engineering with Specialization in Data science has become essential to cater the growing need for professionals and researchers to deal with the future challenges. You can go for a Masters in Science in fields like Telecommunication Engineering, Microelectronics & VLSI Design, Electronics Design and Technology, Wireless Communication, Signal Processing, Robotics, Embedded Systems or VLSI System Design. If you aspire for managerial roles, you can go for a Masters in B
Research and development
Electronics engineers can follow the M. Tech- Ph. D- Research path innovation and development is what interests them. Organizations like ISRO, DRDO, SAIL and BHEL lead in the research field and are ideal workplaces to engineer new and better technologies for the enhancement of the communication and signal systems.
hope this information was useful .
thank you .
So you can have a rough idea about the two courses but which one is better is something only you can decide as you will know better which subject interests you more.
Hello Apu sarkar, Both the Universities are best for bsc and infastructure is also good but facilities are more in TIU like sports campus, wifi campus, and many more and they all are not in MAKAUT and placement is also good at TIU. So I personally preferred you to go for TIU.
Hope it will be helpful for you :)