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Clay's Career Journey: From Pharmacist to Data Analyst

Clay's Career Journey: From Pharmacist to Data Analyst

2 min read

John Pauler

Partner & CRO

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Clay's Career Journey: From Pharmacist to Data Analyst

Clay Cooper spent a decade as a pharmacist before reinventing himself and pursuing a career in data.

The steps Clay took to realize his new dream are filled with fantastic lessons that anyone can apply towards launching their own career.

From my perspective, these are some of the things Clay did right...

1. He started off by doing research

  • He looked to see what types of job opportunities were out there.

  • He made a list of resources he could learn from.

2. He decided to learn by doing

  • Clay realized getting his hands dirty was the best way to learn

  • He specifically sought out opportunities to practice

3. He set specific learning goals

  • After he realized he loved data viz, he set a goal to build one dashboard per month.

  • In each monthly dashboard build, he tried to do somethign that was new to him, forcing himself out of his comfort zone.

4. He shared his learning experience publicly

  • Every time Clay did another data analysis project, he shared it on LinkedIn.

  • This allowed him to build a brand, network, and get feedback from the data community.

  • He also hosted his projects on his own project portfolio website, so it was very obvious that this was a true passion of his.

5. He used one of his projects during the job interview process

  • This was a great way to show what he could actually do

  • He was offered the job the day after his interview

Last but not least, Clay maintained an amazing attitude throughout his entire learning journey. He stayed positive, had the humility to be okay with starting over as a beginner, asked for help and feedback, and expressed gratitude when he received it.

With the way he put himself out there while he was learning, I felt like I knew Clay before we ever met.

And because he was always positive, humble, grateful, and clearly passionate about the career pivot he was trying to make, I (and lots of other people) wanted him to succeed. This is an example of a guy who makes it very easy to like him, and to want to get in his corner.

If you want to break into a data career, or really any kind of career, take what Clay has done as a roadmap.

In his own words...

If you put forth the effort, develop the skills... technical, communication, and personal skills that you need, you can do it. It's not rocket science as far as the method on how to do it. You just have to build yourself a portfolio, and a platform, and just get out there and get your hands dirty, and success will come. It's just a matter of time.

We are very happy that Clay was willing to share his excellent advice to help inspire others on their data journeys. Check it out in the video below!

On behalf of everyone at Maven, thank you Clay!

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John Pauler

Partner & CRO

John brings over 15 years of business intelligence experience to the Maven team, having worked with companies ranging from Fortune 500 to early-stage startups. As a MySQL expert, he has played leadership roles across analytics, marketing, SaaS and product teams.

Frequently Asked Questions

What is Maven Analytics?

Maven Analytics is an online learning platform that helps professionals and organizations build practical data and AI skills in analytics, business intelligence, and data science. Our hands-on courses are designed to help learners stay competitive and future-proof their careers in the age of AI.

Are data analysis and data science still good career paths?

Absolutely. As long as companies collect and use data, they need people who know how to turn that data into results. Roles are changing, and so are the skills needed to succeed, but the career paths remain strong. Focus on data literacy fundamentals, business thinking, communication skills, and learning how to use modern data and AI tools, and you can build a strong career.

Will AI replace data jobs?

AI is changing how data professionals work, but it is not replacing the need for skilled analysts and data scientists. Instead, AI is becoming another tool in the data workflow. Organizations still need people who can ask the right questions, interpret results, communicate insights, and apply data to real business decisions. The most successful professionals will be those who learn how to combine core data skills with modern AI tools.

How can I future-proof my career in analytics?

Future-proofing your analytics career means building strong core data skills, understanding business context, and learning how to work effectively with AI rather than compete with it. The goal is to become a better analyst, problem solver, and decision-maker.

How long does it take to build job-ready data skills?

That depends on your starting point and goals, but many learners can build meaningful skills over a few months with consistent practice, even when studying part-time. The most important factor is applying what you learn through hands-on projects and real business problems.

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