Source: "The top skills needed for a data career" - Google Advanced Data Analytics Professional Certificate

Ideal qualities for data analytics professionals

You have been learning about skills that can help you enter and excel in the data career space. In this program, you will be building technical abilities, which are necessary before pursuing opportunities in data analytics. Job postings will include a list of the required technical skills prominetly displayed. Quite often, organisaions will also make note of additional skills and traits that go beyond working with data on a computer. In this reading, you will explore examples of additional skills and traits that employers are seeking when searching for data analytics professionals.

As you begin to search for job opportunities, many employers seek additional skills that are not exclusive to digital fields. In the sections below, you will learn more about these traits through excerpts found within data analytics job postings.

Being coachable

Coachable individuals are capable of receiving feedback and using that information to make improvements. At the center of being coachable is a positive attitude, and the ability to self-reflect and take steps to grow. People who are coachable usually have a growth mindset, which is a belief that hard work and determination can make them better. As a result, they view feedback from colleagues and supervisors as an opportunity to improve their skill set.

A pssion for data analysis

Employers often seek candidates whose commitment to data analysis extends beyond their professional duties. Volunteering your data skills to help a nonprofit organisation is just one example, but it’s not they only way to show your commitment to data analytics. Data analysis is applicable outside of the workplace, but is often not obvious. Community projects, helping a local school organise data, and developing your own side project are a few examples of how you might demonstrate your passion for data analysis outside of the workplace.

Another way to explore your passion for data analysis is to connect with other passionate data analysts and take on data callenges. A great website for exploring data analytics is Kaggle.com, which hosts an active online community for data scientists and machine learning enthusiasts. Users can collaborate with other users, publish datasets, use GPU-integrated notebooks, and compete with other data scientists to solve data science challenges. Participating in activities hosted by an online data science community like kaggle can add fuel to your passion ofr dta analysis and procide artifacts for your portfolio.

Employers are seeking passionate candidates. Job postings that identify candidates that have a passion for data analysis often include language like:

  • Seeking a passionate data scientist.
  • We seek a candidate with deep curiosity directed toward diverse research interests.
  • Driven. The prospect of focusing on corporate environmental impact as a data domain excites you, and you are personally motivated.

Pro tip: Include in your portfolio your passion for data analysis. Procide examples of passion projects, volunteer work, or analysis outside of employment to relay your commitment to data analysis. If you are conducting data analysis in your free time, it says a lot about your passion.