This Is the Only Way to Become A Data Scientist Without Any Experience

Work your way up to top data scientist jobs by following these steps.

A data scientist collects and cleans large amounts of data, maintains dashboards, interprets data to solve problems, run experiments, build algorithms and presents visualized data to stakeholders. If all that interests you, here's some news for you, you can become a data scientist without experience.

You Don't Need Any Advanced Degrees To Become A Data Scientist

Although most of the job postings that you will come across will mention a master's degree or a Ph.D. in engineering, computer science, mathematics, or statistics, it's possible to land a job without any of that. There are plenty of online courses and certification programs that can give you the knowledge.

Step 1: Work On Your Math Skills

If you have a quantitative background, the switch from your old job to data science should be easy. But before jumping on to high-tech tools, getting the basics right, like plotting data points on graphs and finding correlations, is important. As a checklist, these are the things you should build a solid base on:

• Statistics and probability
• Multivariable calculus
• Linear algebra
• Hypothesis testing
• Descriptive statistics
• Regression analysis
• Markov chains

Step 2: Learn The Important Programming Languages

To be a data scientist, it's important to know and master the necessary skills rather than getting a shiny degree from a university. The interview process is skill-based and these are the languages you need to master:

• Python – Knowing this will help you filter and transfer big data and unstructured data. Python can be used for web development, software development, deep learning and machine learning.
• R – An open-source programming language, R is useful to calculate complicated mathematical and statistical problems. It will also help in data visualization.
• SQL – This is a relationship management tool through which you can query and join data across multiple tables and databases.
• SAS – Large corporations use this tool for statistical analysis, business intelligence, and predictive analysis.

Step 3: Build Your Resume With Internships

Companies look for people with practical experience. Once you have the basic knowledge puting that to work in real-life and dealing with work problems will make your case stronger and impress recruiters with real-time skills. These internships are easy to find as the criteria for internships start with no-basic experience.

Step 4: Start By Being A Data Analyst

Firstly, a data scientist and a data analyst are two different professions. Data analysts manage data collection and identify data trends, while data scientists also interpret data along with using coding and mathematical modeling. Hence, a data analyst role is the best way to launch yourself in the field.

Step 5: Have A Reason For Your Switch

Data science is a booming field and many might be having the idea to switch due to lucrative job roles. However, you need to be able to explain your career transition. Mention your past roles in such a way that you highlight the common aspects of the field. If you are a pro at using Microsoft Excel or developed business, communication, and collaborative skills, mention those skills and explain how you have improved on them to apply in this job.

With all these in mind, you can become a data scientist without experience. Another important thing to keep in mind is to network with people who can influence your position in this field. The more you network, the more opportunities will knock your door.