How to become data scienctist if you are non cs student?

A data scientist is a person who does research part on projects to be able to process big data using the tools of technology, mathematics, business, and communications. Companies use this information in better decision-making, solving complex questions, and growing better. They are responsible for collecting, analyzing, and interpreting large and complex data sets to identify patterns, trends, and relationships that can help organizations make informed decisions.

Through this blog, let us discuss various questions that people ask about a data scientist like how to become a data scientist or how to become a data scientist if people are non-CS students.

How to Become a Data Scientist?

Data scientists typically work with large data sets using tools such as programming languages (e.g., Python, R), statistical modeling, machine learning, and data visualization techniques to make sense of the data. They are required to work along with people in an organization to identify key questions in a company and develop data-driven solutions that can address those questions.

The following measures could be followed to become a data scientist for a student, in general like having some education in the domain:

• While it is not necessary to have a CS Degree, one has to have the knowledge about the domain from somewhere. It could be a Bachelor’s Degree, a Master’s Degree, a Data Science Bootcamp or Online courses etc.
• People must have certain skills if they wish to become a data scientist as these skills majorly are: A Programming Language like Python, Statistics, Machine Learning, Data Visualisation, etc.
• The interested people should be having some hands-on experience in the domain like they either could do their own projects or interact and communicate with other data scientists or they can contribute to the Open Source Projects as well. This Experience helps to have confidence in their work as well as give a selection criteria for the companies that would hire them.
• Once student’s are done with all the skills and experience along with the knowledge about the domain, then they can be hired easily by hiring companies. Hence, they can apply for companies’ hiring or giving certain placement tests that may be a criteria for initial selection in many companies.

You can also refer to our existing article – How to Become Data Scientist – A Complete Roadmap

Why to Choose A Data Scientist Role?

Data Scientist is one of the highest paid jobs in the country and apart from this there are a number of Pros that people can look at when they talk about pursuing a career in this field and some of them could be mentioned as:

1. High in Demand : If people choose data science for their career path then they can be assured that there is no shortage of opportunity for data science careers because nearly every industry is looking for data scientists, particularly those with a strong set of skills.
2. Data science is a fast-paced field: The speed at which data science changes can be exciting, but this also means that people need to keep up with new advancements, tools, and best practices. So, these people must assure that they can adapt to all the changes and learn new skills as per change.
3. Exceeding Job Capabilities: A job in data science is both demanding and useful to people’s resumes where people are needed to solve problems and help companies or society in developing technology that can result in better decisions using data because data is the new fuel of the next generation and a career in data science always improves the capabilities of people who are involved in this industry.
4. Productive Work: Data science is used to create work from the things that are not effective at starting hence utilizing the power that the data beholds and all of the information gained during the handling of data helps in decision making and other important solutions during growth of a company.
5. Diverse Career Paths: Data science offers a variety of jobs to people and this is one of the reasons why people must pursue this as their career. By learning data science people can learn about different job roles which come under this field.

Technical Skills Required for Transition into Data Science

There are a lot of skills which are required by people to become a data scientist but some of the Major technical skills that are required by people to switch their career from non CS to Data Science are as follows:

1. Programming: Python is an essential in the field of Data Science and it simply is used majority of times due to its number of libraries like NumPy, pandas, Scikit-learn, and TensorFlow, this language allows data manipulation very easily. People who don’t like python language can also prefer R language. People should learn how to efficiently handle the datasets that are further analyzed in Data Science. Also, people must learn about the transformation of Data, handling of missing values, and inconsistency, and many more.
2. Maths and Statistics: One should be having a great statistical foundation with concepts that include Probability , regression analysis , time series analysis and hypothesis testing and some of the other mathematical concepts that are important for people are Calculus, Linear Algebra, etc.
3. Machine Learning: Understanding algorithms based on machine learning is a must do thing in data science and some of the examples of these can be linear regression, decision trees, k-nearest neighbors, and support vector machines.
4. Some libraries: There are a lot of libraries provided by python and apart from Numpy, Pandas, people must also have knowledge about applications like Tableau and PowerBI which also come into picture in today’s data science field.
5. Frameworks or other skills: A data scientist should possess skills in designing, training, and fine-tuning neural networks for various use cases, as well as knowledge of different neural network architectures and frameworks.
6. Learning DevOps: Devops is a technique of developing software that places a strong impact on teamwork and communication between the development and growth teams and it is an important part of the roadmap for becoming a Data Scientist.
7. Understanding Tools: Analytical tools are one of the most helpful data scientist skills for extracting valuable information from an organized data set like SASHive, Pig, R etc are the most popular data analytical tools that data scientists use and learning these skills help in Data Analysis.

Non-Technical Skills Required for Transition into Data Science

Along with the technical data scientist skill set, data scientists also require certain non technical skills in their journey. These can be personal skills and it can be difficult to get simply by looking at educational qualifications, certifications, and so on and hence are very important to look for. Some of these skills include:

1. Business knowledge: The best way to productively utilize technical skills in the picture is to have strong business knowledge because without it, data scientists may not be able to address the problems and main difficulties that come in their way. These problems need to be solved in order for an organization to grow and this is important for helping people to explore new business opportunities.
2. Strong Communication Skills: Another thing required for the top of data scientists is communication skill because data scientists clearly understand how to extract, understand, and analyze data. But, for people to be successful in their career, and for companies to grow and benefit from people’s work, they should be able to successfully communicate their opinions with fellow team members who don’t have the same professional background as them.
3. Data Intuition: This is maybe the most significant non-technical skill a data scientist can have as valuable data insights are not always relevant in large amounts of data sets, and a skilled data scientist has intuition and they know when to look and think out of the box insightful information. This makes data scientists more efficient and productive in their work, and getting this special skill comes from experience and the right training. Also, people can also become experienced by doing a lot of bootcamps or live projects.
4. Ability to Analyze Data: The capacity to handle data and its analysis is one of the things that a data scientist has to learn in their journey of while learning data science.
5. Creative Thinking: Using innovative thinking and design thinking to come up with great ideas and answers to unanswered questions.

How To Become Data Scientist if you don’t have a Data Science Degree?

People who want to become a data scientist even if they don’t have a computer background then they can follow the given step by step guide given to become a Data Scientist:

• Step 1: Start by enrolling into a Online Data Science course.
• Step 2: Learn the basics to have the foundation for advance knowledge in the domain of Data Science.
• Step 3: Get Familiar with the required programming languages, math, probability, and other requisites for the domain.
• Step 4: Gain Hands-On Experience by doing some projects relevant to Data Science.
• Step 5: Apply for Data Science jobs in the companies offering desirable roles.

How Much Do Data Scientists Earn?

Data Scientists in India earn about 12 Lakh per annum on average,as the Average Base Pay range is 7-19 Lakh per annum and if progressed rightly Senior and Lead data Scientists for companies can earn upto about 25-30 Lakh per annum.

Some Data Science Jobs and Roles

Some Jobs and their respective roles in Data Science could be listed as:

1. Data Analyst: In this job role people need to access and clean data, perform statistical analysis, and get visualizations to the company.
2. Data Scientist: People must analyze Data, build, train and tune ML models for reliable predictions of the future.
3. Data Engineer: People needs to design and maintain data management systems for research.
4. Data Architect: People here create the blueprints for data management for ease of integration, centralization, and encryption.
5. Data And Analytics Manager: People are asked to develop strategies and look after the operations, assigning the respective duties to the team according to skills and expertise.

Conclusion

From the above blog, it is clear that this job of being a data scientist is as rewarding as the job could be and it comes with learning a lot of things and experience of applications in this particular field. Whether people are from computer background or from non-computer background they can become a data scientist.

For people who belong to non computer background requires a little more additional skills that are already taught to students who belong to computer fields. This blog also contains how non CS people can transfer their career to data science and can happily become a data scientist by learning just a few necessary things.

How to Become Data Scienctist If You Are Non-CS Student? – FAQs

Q1. What coding language can be used as an initial point in Data Science?

Python or R can be used to begin the journey of becoming a data scientist but the majority of people prefer python because of its huge libraries.

Q2. Is data scientist a highly paid job in India?

Yes, People with some experience and good skills can get a job at a higher position with a high salary.

Q3. Can one become a data scientist without being in cs background?

Yes, if people can follow proper roadmap and show dedication then they can easily transform themselves from non cs background into Data Science domain.

Q4. Can freshers join as data scientists?

Yes, people can become a data scientist even if they are freshers as there are a variety of applications in the field of data science and for which a lot of job opportunities are there.

Q5. In how much time can people become a data scientist?

For people to become a data scientist can be a challenging task and this can easily take 2-3 years for completing the roadmap and becoming a successful data scientist by joining as a fresher.