Big data managers with a unique combination of skill sets are known as data scientists. You won't be able to get a top job as a data scientist by focusing simply on your technical education.

If you want to know more about the top ten data science qualifications for a Data Scientist job interview or your current position, keep reading. You can also check out extensive Caltech Data Science Program to help you get started.

Top 10 Data Science Qualifications

Potential data scientists will have a solid foundation if they are qualified in the data science skills listed below.

1. Programming

Programming skills are required to become a data scientist. Languages like Python, SQL, and R are frequently used by data scientists. Data Scientists don't require a deep understanding of programming as a software developer does. As long as you can produce effective code in any language, having a fundamental understanding of the language is sufficient to land a position in data science.

Become a Data Scientist With Real-World Experience

Data Scientist Master’s ProgramExplore Program
Become a Data Scientist With Real-World Experience

2. Probability and Statistics

In data science, knowledge, insights, and well-informed decisions are extracted from data using sophisticated procedures, algorithms, or systems. In such situations, drawing inferences, estimating, or making predictions play a key role in data science. Estimates for additional investigation can be made using probability and statistical techniques. The theory of probability is the main foundation of statistics. Simply put, both are connected.

3. Mathematics

Another critical component of data science is mathematics. Linear Algebra, Calculus and Optimization Theory are three subjects in which you must be knowledgeable if you want to become a skilled data scientist.

4. Machine Learning

Machine Learning is a fantastic method for analyzing vast volumes of data, which makes them a crucial component of any profession of data science. It can assist in automating many of the duties associated with a Data Science position. To begin a career in this industry, comprehensive knowledge of machine learning techniques is not necessary.

5. Visualization

One of the more critical skills is data visualization because it goes beyond simply displaying the findings to understanding the data and its limitations. Visual representation of concepts is always preferable because they are more well-known and understood. When done by a data visualization professional, graphics can effectively communicate a message. Before moving on to more complex charts, you must become familiar with basic graphs like bar charts, histograms, and pie charts.

6. Big Data

Due to the rapid rate at which data is being produced, analyzing and dealing with massive amounts of data has become a regular aspect of a data scientist's job. Big data is a crucial part of data science. As the name suggests, big data is used to gather, scrape, and analyze extensive sets of data. Processing humongous amounts of data is not possible manually or either by any computational power. Big data is one such technology that can help data scientist to do their job proficiently. 

7. Web Scraping

The ability to scrape any online data exists, technically. Utilizing this technique, businesses can extract vital data, including text, photos, videos, and other types of information, in order to boost productivity.

8. Cloud Computing

Massive amounts of data are examined and analyzed by data scientists every day. Data scientists are able to take advantage of operational tools, coding languages, and database systems thanks to the use of platforms like AWS, Google Cloud, and Azure.

9. Deep Learning

Deep learning is one of data science's most important aspects, including statistics and predictive modeling. Data scientists who collect, analyze, and interpret vast amounts of data benefit from deep learning's ability to make this process faster and easier.

10. Business Intelligence

Data scientists must be well-versed in business strategy in order to discover insights that will genuinely benefit stakeholders and decision-makers. Any reputable data science boot camp will teach you these skills as part of its curriculum, and you'll learn a lot more on the job through hands-on training.

Become a Data Scientist With Real-World Experience

Data Scientist Master’s ProgramExplore Program
Become a Data Scientist With Real-World Experience

Here’s How You Can Become a Data Scientist?

Formal education is typically necessary to become a data scientist. Here are a few steps to think about.

  • Get a Degree

To get an advantage in the profession, consider pursuing a relevant bachelor's degree in data science or computer science.

  • Take a Course

A recognized course or a data science boot camp such as Simplilearn’s Advanced Certificate Program In Data Science are excellent places to start if you want a thorough, hands-on education in both the field of data science and the job of a data scientist.

  • Acquire Practical Knowledge

It won’t matter if you have passed your degrees with flying colors, if you don’t have practical experience. Try to be a part of projects that build your portfolio. Practical experience is given more importance when you step out to get a job.

  • Create a Network

Networking plays an important role in today’s world. Anyone who is a fresher or has started a career in data science should connect to people who have already established themselves. Connect with such people on LinkedIn or other social platforms. This will help you to find job opportunities and practical projects.

  • Get Ready for Interviews

Research is essential while preparing for a data science interview. Study the business, the people, the position, common data science interview questions, and follow-up questions to ask the interviewer.


Being well-qualified is one approach to ease interview anxiety and boost confidence because data science demands a lot of work. Consider doing Simplilearn’s Data Scientist Master’s Program to enhance your skills.


1. How many years does it take to become a data scientist?

A fresher with absolutely no experience in coding can enter the field of data science if he takes up a professional course that spans almost nine months to a year. 

2. Are data scientists in demand?

Data science is a fantastic career with much potential for future growth. Already, there is a lot of demand, competitive pay, and several benefits.

3. How can I be a data scientist after the 12th grade?

Students who have a computer science, engineering, or related technical background select data science classes after the 12th grade.

4. Which degree is best for a data scientist?

Computer Science or mathematics degrees can be considered the best to become a data scientist.

5. How do I start a career in data science?

Getting a degree or certificate can be an excellent entry point for anyone interested in a career in data science.

Data Science & Business Analytics Courses Duration and Fees

Data Science & Business Analytics programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Data Analytics Bootcamp

Cohort Starts: 24 Jun, 2024

6 Months$ 8,500
Post Graduate Program in Data Analytics

Cohort Starts: 8 Jul, 2024

8 Months$ 3,500
Caltech Post Graduate Program in Data Science

Cohort Starts: 8 Jul, 2024

11 Months$ 4,500
Post Graduate Program in Data Science

Cohort Starts: 11 Jul, 2024

11 Months$ 3,800
Applied AI & Data Science

Cohort Starts: 15 Jul, 2024

3 Months$ 2,624
Post Graduate Program in Data Engineering

Cohort Starts: 16 Jul, 2024

8 Months$ 3,850
Data Scientist11 Months$ 1,449
Data Analyst11 Months$ 1,449