How to Become a Data Science?
Steps to Become a Data ScientistA data scientist uses their programming, analytical, and statistical skills to collect, analyze, and interpret data sets. This information helps them develop data-driven solutions to a variety of business challenges. Data scientists also have a large array of technical competencies including reporting technologies, machine learning, databases, coding languages, machine and statics learning. Here are five steps on how to become a data scientist.
Get your undergraduate degree in data science.
The first step to becoming a data scientist is to obtain your undergraduate degree in data science or another closely related field. To get your foot in the door, most employers will prefer to see a bachelor's degree at a minimum. Honing the skills necessary to complete your work will help prepare you for your future as a data scientist. Possible courses of study include:
- Computer science
- Data science
An internship following the completion of your schooling will help you dive deeper into what life will truly be like after you begin working as a data scientist.
What type of degree should you pursue to become a Data Scientist?
64% of people working as a Data Scientist earned a Bachelor's Degree
What skills do you need to be a Data Scientist?
- Machine Learning
- Natural Language Processing
- Hadoop SPARK
- Programming Languages
Sharpen your skill set.
Learning the necessary skills to become a successful data scientist will make you proficient in your chosen field. You can expect to be required to know machine learning techniques, programming, data visualization and reporting, effective communication, risk analysis, big data platforms, and other skills necessary to be efficient at the job.
Develop skills in database management, artificial intelligence or machine learning.
Specializing in a particular industry is a great way to increase your opportunities for higher earning potential. Developing your skills in specific fields such as database management, artificial intelligence, or machine learning can help open those career paths. As this emerging career path grows, more opportunities and career paths are emerging, and specializing your skills may be vital as you look for a data scientist job.
Analyzing, sorting, and managing large chunks of data are key components used by data scientists. Programming languages for data science include:
Data scientists need to have the ability to create graphs and charts. Data visualization tools for data science include:
Data scientists also need to have some essential machine learning, big data, and communication skills to succeed in their field.
Find a job.
Do some research and find a job that can help you develop your skills and work toward becoming a data scientist. Entry-level positions such as a business intelligence analyst, data engineer, or statistician can make it possible to work your way up to become a data scientist as you further expand your skills.
Further your education.
While a bachelor's degree may be enough to get you started in the right job and earn necessary real-world work experience, a master's degree in data science might be essential to excel in your field. If you plan to pursue a master's degree, continue to work in your entry-level position or as an intern; this job experience can make you more attractive to an employer for a high-level position. Possible master's degree programs include:
- Master of Applied Data Science.
- Master of Science in Data Science.
- Master of Computer Science in Data Science.
- Master of Data and Network Analysis.
A master's degree will open up additional career opportunities and increase your potential salary as a data scientist.
Data Science Career Path
Senior Data Scientist
Lead Data Scientist
Total Pay Trajectory
Data Science Career Path
Related Careers in the Research & Science Industry
Interested in other Research & Science careers? Below are occupations that have high affinity with Data Science skills. Discover some of the most common Data Science career transitions, along with skills overlap.