Every industry relies on data science. Whether it’s improving the customer experience via marketing and communications to the newest healthcare technology industry, nearly all modern industries rely on data science to make decisions.
Careers in data science are becoming more popular and the world of eCommerce grows, and that trend doesn’t look to be changing anytime soon.
Here are the Top 5 Data Science Careers:
1. Data Analyst
A data analyst is exactly what it sounds like — a job where you analyze data. However, it requires a bit more than a love for data. Data analysts look at business data for an entire organization, a department, or even a team and then distill that data into digestible analyses or solve problems related to that data.
One of the easiest places to start if you’re interested in a career in data analysis is to offer to be the employee who reviews your company’s Google Analytics. You can take the information you glean from the Google Analytics about your company and turn it into insight you can put into practice.
There has been a big increase in demand for people who excel at analyzing a company’s website analytics as it helps to see what things need to change and things are working for the company currently as it relates to their site. As you probably know, Google pretty much rules the internet so knowing how their analytics work is always going to be a plus in the data science world, and this offers valuable hands-on experience.
2. Data Architect
If your love for data coincides with a love of creating things, a data architect might be the job you’re searching for. A data architect builds programs that are designed to store large amounts of data. They also use computer programs to organize the data in a way that makes sense as well as identifying the data they need to determine certain statistics or processes.
To become a data architect, you’ll most likely need a bachelors in Computer Science as most of your day to day duties will require a combination of math skills, computer skills as well as communication skills.
Most people don’t consider the important part communication plays in data science careers overall because they are based in math and science. It’s important to remember that while, yes, your main job is analyzing data, you also have to communicate your findings to others in your company as well, often people who have little knowledge of the subject matter.
A statistician isn’t a career only for the sports world. Statisticians play a big role in the world of data science as they’re often the ones responsible for mining data. They’re also key players in voice recognition software like Alexa and Siri.
While you wouldn’t think numbers would be all that helpful in voice recognition, they’re actually critical. For example, programs like Google Translate use data to configure translations online. Those numbers are then maneuvered into sequences that can be matched with certain dictionaries.
Statistics is a tough field that requires a lot of brainpower. Most jobs require Master’s degrees in statistics or mathematics. Although, there are some entry-level positions that only require a Bachelor’s in the same fields.
4. Freelance Work
Just like in the world of copywriters and consultants, data analysts can often find freelance work by looking at job boards, like UpWork or Guru, that are specific to tech work. Many companies don’t have specific positions for data analysts in-house and they often outsource it or look for freelancers in their area. As a freelance data analyst, you can set your own rates and determine the hours you wish to work.
One of the big differences in working in-house as a data analyst versus working as a freelancer is that as a freelancer the company will give you an idea of what data they want mined and analyzed. An in-house data analyst is usually tasked with figuring out what data is needed to begin with but that is often already done for you as a freelancer.
5. Data Engineer
If working with data is something you don’t necessarily mind, but don’t find yourself having a passion for them, a job as a data engineer might be an option. While they still have to use numbers and mathematics in their everyday jobs, a data engineer focuses more on the data infrastructure. This position also requires a lot less statistical analysis.
Data engineers focus more on the computer part of computer science. They develop software and programming skills for the company and actually have a large part in marketing and sales. Data engineers are responsible for building pipelines that collect information on marketing and sales. This relates to everything from branding to identifying a target audience. They then hand this information over to others on the data team such as the data analysts and scientists.
No matter which career in data science seems right for you, it’s clear that these positions are only going to become more valuable. If mathematics and science are both something you enjoy it’s also great to know that data scientists jobs are often some of the highest-paid employees. As we continue to test the limits of technology and computers, positions in data science are going to become more available.
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