Succeeding at Work - What does career success mean to you?
Career Success

Succeeding at Work - What does career success mean to you?

Whether you’re looking to be more productive, move up in your career, embrace work-life balance, or learn a new skill like data management, we’ve got expert advice that will make you more successful at every stage of your career.
 
Are you looking for a career with a significant amount of potential and opportunity for your career?

One career path you’ll definitely want to explore is data and analytics. The top three jobs with increasing demand across the life science industry are data analysts and scientists, AI and machine learning specialists, and big data specialists —all fall under the data and analytics umbrella.

The pharmaceutical and biotechnology industries are expanding and are only just now at the cusp of realizing massive investments into becoming more data-driven industries.

This means that they are and will be hiring tons of data-savvy people with good communication skills. So, what can you expect as a prospective data analyst or scientist?
 
Clearly, there are opportunities in data and analytics. But the question is, are these roles right for you?

Should You Pursue a Career in Data and Analytics?

If you like solving problems, love to code and are at your best when you’re always learning something new, this job is for you. If you’re fascinated by data and numbers, you might enjoy using them to help companies succeed through a career as a data analyst.
 
You also know that it’s a pretty in-demand job at the moment and that even if you’re not passionate about breaking into a data science role, there are some data science skills worth having in your pocket (and on your resume).

As Silvia Martins, CEO of Five Validation points out in her article on Data Integrity In the Pharmaceutical Industry, "data integrity has led to risks to the safety, efficacy, and quality of the products, associated with the breach of trust of regulatory agencies, patients and company shareholders".

"Data that must maintain ‘preserved integrity'. All final data regarding the production process, and metadata, which carry information about the main data and raw data should be a part of the integrity assurance process".
 
Online classes can be a great way to quickly (and on your own time) learn about the good stuff, from Python or SQL to basic data analysis and machine learning. That said, you may need to invest to get the real deal.

In my next article, I’m going to outline some of the highest-rated and most popular courses you can take within the realm of data science—whether you’re looking for a casual overview or a serious deep dive.

These online data science classes—some will be free and short compared to the more comprehensive courses which, if you’re looking to go even further, you might consider a data science boot camp.

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November 17, 2022

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