Why Pursue a Career in Data & Analytics

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It's easy to do well in data and analytics. It's one of the few job markets that favors employees more than employers. It comes with good pay, interesting work, and an abundance of remote work opportunities.

It also offers a wide range of industries to work in. Here is just a sample of the work people in data have accomplished:

• Optimizing the messaging used in advertising
• Predicting box office revenue for new movies
• Identifying police officers at risk of using excessive force
• Predicting hospital patients at risk of sepsis – a life threatening condition

All of these outcomes wouldn’t be possible if it weren’t for the armies of data engineers, data analysts, data scientists, and many others who build programs to track, transform, and analyze the world’s data.

Whether you love programming, analysis, or storytelling, there's a place for you in data analytics.

Would I Enjoy Data and Analytics Work?

You can be certain you’ll enjoy a data analytics career if you answer yes to at least one of the following:

1. Do you like math?
2. Do you like programming?
3. Do you like logic puzzles?
4. Do you like explaining interesting things to people?
5. Do you like finding out why something breaks?

And as I said, it only takes one yes to know whether you’d like a data career. Just because you don’t like math or intensive programming doesn’t mean there isn’t a place for you. There are careers for creatives in data too. And the creative data analytics careers still pay pretty darn good.

What Salary Can I Expect?

One of the most common answers you’ll hear in data science is “it depends.” That same answer applies to the salary you can expect. The biggest factors are what specialization you pursue and whether you earn a relevant master’s degree.

In the midwest and most markets with lower costs of living, entry-level workers with only a bachelor’s degree can reasonably expect $40-50k a year in the analytics space. Some might get lucky and go over $60k.

Someone with 1-5 years experience without a masters degree can reasonably expect between $60-85k. Some might reach the mid-90s. It’s important to grow your technical skills – both in breadth and depth – during this time.

Those with 5-10 years can break the $100k mark provided they do good work and continue to re-invest in learning relevant skills. It’s easy to age out of the marketplace as the technology changes. So don’t get too comfortable with one programming language or tool.

A masters degree will open up higher paying positions earlier in your career.

Typically, you’ll need a graduate degree in statistics, data science, economics, or computer science to be considered. Other graduate degrees, such as an MBA or sociology with demonstrated mastery of statistics or programming, are able to make the transition as well, but they will have to make a strong case for themselves.

An entry-level graduate degree holder could realistically make $70-80k. Someone with a graduate degree and 1-5 years relevant experience could probably make $90-110k. Someone with a graduate degree and more than 5 years experience could potentially make over $120k.

My Experience with Data Science Salary

I can personally attest to these salary ranges. About four years into my career and at the height of the COVID-19 recession, I asked for $85k for report developer roles. I very seldom was asked to lower my salary expectation. Hell! Some recruiters even told me I was too low and said they’d raise it to $90k when making the bid to their clients!

What Qualifications Do I Need?

That also depends! Mostly on the role you want to pursue. A data scientist or machine learning role typically requires a master's degree or a graduate-level certificate.

Typically though, you’ll need to get a bachelor’s degree for most jobs outside of data scientist or machine learning engineer. It often does not matter which degree though. I’ve seen people with English Literature degrees who do just as well as people with mathematics degrees. You will have to work harder to demonstrate your aptitude and skills with a non-STEM degree though.

If you don’t have a college degree, you could enroll in a IT program, such as those offered by Centriq. It’s very common for individuals to enter those programs and earn certification in database or Linux administration and find themselves in a good career afterwards. The same for database and ETL development.

What Job in Data Analytics Should I Pursue?

In my book, How to Manage a Successful Data Team, I talk about the best “types” of people for “data work.” There’s three in particular that I often find in this field:

• Math Geeks
• Programming Geeks
• Creatives

This list is very subjective and it’s not exclusive by any means. It’s also not “one or the other.” Just because you’re a math geek doesn’t mean you can’t be creative. But if there’s one area you’re strong in, there are specific careers in data science you can pursue over others.

Best Jobs in Data Science for Math Geeks

If you are one of the rare people who enjoyed math, statistics, or economics in college, you’re in luck – those are some of the best paying and most in-demand skills in analytics! Some of the jobs you could pursue include:

• Data scientist
• Machine learning engineer
• Data analyst

Data Scientist
Data scientists build predictive models, run statistical analyses, and apply machine learning to business problems. Typically, a graduate degree or enrollment in a graduate program is a job requirement.

Machine Learning Engineer
Machine learning engineers are similar to a data scientist, except they work alongside computer engineers and big data engineers to apply machine learning on a much larger, enterprise wide basis. Just like a data scientist, a graduate degree is often a requirement.

Data Analyst
Data analyst roles are great for getting your feet wet with data work and serves as a good springboard into data scientist roles later. What’s more, you can get these jobs without a graduate degree and you have more freedom to apply data science techniques as you learn them in a less risky environment.

Best Jobs in Data Science for Programming Geeks

There are abundant opportunities in data and analytics for people who love to program or work with computers. The best part is many of the most in-demand data jobs don’t involve math or statistics. Those jobs include:

• Database administrator
• Data engineer / developer
• Web analyst

Database Administrator
Databases are not necessarily easy to set up and manage – much less keep secure. Trust me. I’ve tried and it’s a headache. That’s why many companies hire someone to do that for them, which is what database administrators do. You often need a bachelor’s degree, but I could see people with a tech school background also getting these jobs.

Data Engineer / Database Developer
One thing you’ll quickly learn in analytics is that the data is almost never clean. And it takes a lot of work and planning to move it from one place to the next. That’s where database developers and data engineers (the more fashionable phrase) come in. You typically need a bachelor’s degree.

Web Analyst
Web analyst is a misnomer. They often don’t do much analysis. Typically, they use JavaScript and Google Tag Manager to track user behavior online. Don’t worry. It’s not as creepy as it sounds. It’s typically just the behavior on a website you're tracking and this data is anonymized. I’ve known many people who’ve made a successful career in this field and it’s easy for those without much programming background to break into.

Best Jobs in Data Science for Creatives

Many people are surprised to learn there’s many fun and creative jobs in data and analytics – and that they still pay pretty well.

If you have a flair for design or storytelling, you can pursue one of the following:

• Report developer / data viz developer
• Data strategist

Report Developer / Data Viz Developer
Report developers build automated reporting (often called “dashboards”). People who've never worked in a business environment are often surprised that this is a job, but it's actually a very valuable thing for organizations.

Dashboards reduce a lot of time spend compiling data for reporting purposes. It also helps ensure reporting accuracy since fewer people will handle the data. Business leaders love them too. Especially those that are clean, intuitive, and easy-to-read.

What’s even more amazing is the sub-culture built up around data visualizations. If you ever attend a Tableau User Group, you’ll see many people approach this job like an art form. And best of all, it pays very well compared to other design oriented jobs.

Read more about becoming a Tableau report developer here.

Data Strategist
Data strategists are the “big picture thinkers.” They get to work with key stakeholders to develop a roadmap for their data strategy. Often they get to be the key decision makers for what the data scientists and engineers build.

This is a job that’s often done poorly. Many companies put people who’ve never programmed or worked with data in these roles. If this job interests you, I suggest working a few years in one of the other roles on this list and then pursue this strategy. You’ll be far better than most of the strategists out there!