3 Ways Of Progressing In Your Career As A Data Scientist

 

There are a number of ways to progress in a career as a data scientist. As data is becoming incredibly more useful in day-to-day life and in numerous industries, a career as a data scientist is becoming more and more versatile, so we’ve put together a list of three ways you can progress your career.

Quantative Finance

Data science is one of the key fields that quantitative finance employers look for in potential employees, and so it can be a natural progression for someone with a career in data science. Being a qualified data scientist is already a great first step on the way to becoming a quantitative analyst, a role that comes with very attractive salaries.

An excellent way of gaining the necessary qualifications to become a quant analyst is through a quantitative finance course, such as the CQF (Certificate in Quantitative Finance). This is a cost-effective and useful method of mastering machine learning, trading algorithms, and quant finance.

Also, the qualification that you gain at the end of the CQF is globally recognized, so this is the perfect first step for a professional data scientist who wants to become a quant finance analyst.

Data Engineering

Data engineering involves the management of a company’s entire infrastructure of data, and so focuses more on the computer programming and software creation side of data science, rather than focusing on mathematics and statistical analysis.

The responsibilities of a data engineer involve being in charge of creating data systems that provide all the necessary data such as revenue, marketing, and sales information to all the relevant people such as analysts and data scientists.

Some of the skills you need to be proficient in to become a data engineer is fluency in programming languages such as Java, C++, Python, and experience with database managing programming languages such as SQL

This can be a very lucrative position to hold, as the companies who hire data engineers are often large corporations that have extremely large amounts of data to process.

Database Administration

A database administration role is a key data science role for those with experience in admin roles. A database administrator is responsible for the running of a company’s database and is directly responsible for allowing and denying users from within the company access to the database. This can be vital in many companies, as the data they store can be extremely sensitive.

To become a database administrator, you must be able to show that you have experience with data security, data engineering, backup/recover systems, and experience with HR and disaster management wouldn’t go amiss.

In Summary

As data science becomes more important as the years roll by, it is important to keep adapting to the field, and ensure you keep learning and gaining new skills, experience, and qualifications.

With such variety and versatility when it comes to the selection of roles available in data science, it will not be difficult to find a role that is suited to your capabilities and most importantly, a role that you enjoy.