Thursday, July 7, 2022

Essential considerations for a data scientist career path


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According to a report by the U.S. Bureau of Labor Statistics, 11.5 million new jobs will be created in the data science field by the year 2026.

Many individuals want to be a part of the data scientist career path, but they are clueless about how to get started. Most of them think that they can’t be one because they don’t have an advanced degree or a specialisation with a data science subject in their formal education. But that is not the only way to become a data scientist, there are many other aspects, where one can focus on, to launch their careers in data science.

Role of a data scientist

Data scientists are analytical experts who work with business stakeholders to understand their goals and determine how data can be used to accomplish those goals. They combine computer science, statistics, and mathematics to process, analyse huge sets of structured and unstructured data. Then they share insights with peers to create actionable plans for the industry. Here are the key tasks and responsibilities of a data scientist:

  • Acquire, process, clean, integrate, and store data
  • Building models to solve business problems
  • Discovering new algorithms and developing programs to automate repetitive work
  • Presenting information with the help of data visualization techniques
  • Employ sophisticated analytical, statistical methods, and machine learning to prepare data for applying in predictive and prescriptive modeling.

Skills required for a data scientist

Let’s understand an outline of the skills required for data scientist and start working in the big data industry.

· Polish math skills

Mathematics is considered one of the key subjects when it comes to be data scientist. It is very crucial in the field of data science as there are several concepts related to it in data science. Also, concepts like statistics and probability theory are vital for algorithm implementation. So, make sure to put in a lot of effort into sharpening your mathematical skills as it will help to write efficient code and get accurate conclusions. A few highly recommended math concepts that are used vastly in the big data industry are:

  • Statistical methods and probability theory
  • Probability distributions
  • Linear algebra
  • Hypothesis testing
  • Statistical modeling and fitting
  • Multivariable calculus
  • Data summaries and descriptive statistics
  • Regression analysis
  • Bayesian thinking and modeling
  • Markov chains

· Learn programming languages

When it comes to data science knowledge of programming languages is very important. One can enhance their programming skills by being a certified data scientist. Build a strong foundation in any of the programming languages. Keep your complete focus on them. The interview process for data science jobs is totally skill-based so master the following:

  • Python
  • R
  • Java
  • SQL

· Take up an internship

Internships can be considered as the best way to gain knowledge in data scientist career path. In the process of job hunting, being an intern will give you a real-world experience using real-world data. These are very helpful especially when you don’t have any previous experience or any kind of advanced degree. During your internships, you will get to interact with others who would have years of experience in data science. You can learn, understand as well as implement the best solutions. This will positively impact your career and also increases your chance to get a good job opportunity as a data scientist.

Role of certification programs

Being a certified data scientist plays a vital role as it enhances the skills of an individual. In this article, let’s understand some of the career options in artificial intelligence, skills that are required in the fields of ML and AI. And the industry-recognized top certifications.

Certifications are very helpful to get a better job and also to be stand out from the competition. A certification program will add a great amount of value to one’s career in the following ways:

· Develops skills

By doing a certification one can get the knowledge depending on the latest industry standards, tools, and technologies. The demand for capable big data professionals with deep analytical, interpretation, and data management skills has grown exponentially. And many organizations are looking for people who have the right kind of skills and certifications. It can be said that in the present competitive world the people who can exhibit their skills and who have certification will have a fulfilling career.

·  Better salary

The growing need for talented candidates in the data science field has made many firms offer better salaries to the right talent. Many firms consider the certifications as a benchmark to review a candidate.

A technologist from the United States. Troy has worked with several major financial organisations implementing IBM mainframes.

Troy Beamer
Troy Beamer
A technologist from the United States. Troy has worked with several major financial organisations implementing IBM mainframes.

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