From Math Teacher to Data Analyst: How I Transformed My Career

Leaving the world of education behind him, Nick transformed his career from high school math teacher to data analyst at insurance brokerage, Lockton. Here’s how he did it.

by Alison Ward on 25 July 2022

Nick Logan, a CareerFoundry data analytics graduate

You might think that a background as a math teacher is a good foundation to transition into a career in data, and you’d be right—but it’s not essential. In fact, it wasn’t exactly a natural progression for Nick, who spent three years in education before swapping teaching for tech.

Realizing a lifetime spent teaching wasn’t for him, Nick turned his attention to the world of data: an accessible and lucrative industry, without the need of a university degree in order to thrive.

Putting in a lot of dedicated hours, Nick completed the Data Analytics Program with CareerFoundry, created a data analyst portfolio from scratch, and prepared himself for a job search in a brand new industry. He dusted off his networking skills and landed his first job in his new field industry at insurance firm, Lockton, where he’s now working as a data analyst. I was lucky enough to chat with Nick to learn all about his career change. So, without further ado, here’s his story…

Hi Nick! Thanks for chatting with me today. What led you to pursue a career in data analytics after teaching?

Hey Alison. Sure. So, as you mentioned, I started out my career as a high school math teacher and I was teaching for three years. A month or so after the winter break of my third year, I began to realize that I liked teaching, but I knew it wasn’t the career I wanted to have for a lifetime. 

That was the impetus to start looking elsewhere. Data analytics was appealing because it was a field that seemed pretty accessible for me: I didn’t need to go back to school to retrain, and I could build on the skills I already had. I finished the school year before leaving my job and signing up for the Data Analytics Program with CareerFoundry, and I was able to work a part-time job at a fitness club while studying. The flexibility of the program was really great for that.

What was it that drew you to CareerFoundry and the Data Analytics Program? 

One of the biggest things that appealed to me about CareerFoundry was that it boasted successful career change, and it was accessible for those who weren’t necessarily in the tech field yet.

I did a decent amount of research to try to find the right program. Another thing that stood out was the price point, honestly. A lot of other offerings that I was looking at were bootcamps through universities, and they had university price tags—they were at least three times as expensive as CareerFoudry’s courses. 

I also thought that some others around the same price point (or cheaper) weren’t as robust as CareerFoundry, so from a value perspective I thought it was the easy standout. 

Another thing that I really liked—that I’ve touched on already—is the flexibility. A lot of those university bootcamps had an in-person class or an online class that you had to build into your schedule, often for the same time every week. 

A quote from data analytics graduate Nick about his career change journey

How did you find the balance of working part-time while studying? 

Taking the time out to do the course felt a bit like I was taking a really long summer break, like I used to have when teaching! At most I was working maybe 35 hours a week at the fitness club, and that didn’t happen often with my shift pattern. So studying and working part-time felt really doable, especially if I sat down and mapped out the current section of the course that I was working on. 

You’ve mentioned a lot of pros about the program so far. Was there a particular challenge that you faced during your studies? 

From a time-budgeting perspective, I’d say it was hard to forecast or predict how long it would take to do certain exercises or lessons at times. Usually before starting a new task, I’d set a goal which I wouldn’t necessarily meet, but then maybe the next one I would finish ahead of time. So it did kind of balance itself out, but it would have been helpful to have a rough time estimate on the entire section, or a difficulty rating, to know from the outset how much time to set aside. 

Can you tell us about your mentor and tutor?

If I had a quick question, I’d write to my tutor. But if I wanted to hop on a call and hash something out that was more conceptual—or something that I wasn’t quite understanding, or even if I wanted to chat about the industry itself—that would be with my mentor. 

I had a lot of fruitful calls with my mentor. Whenever I turned in a final project, we’d have a call and go over it together. That was a good way to reflect on my work. I’d learn what to tidy up if I were to do it again, or be able to apply some of the notes he gave me to my work going into my portfolio. 

Now that I mention that, the portfolio was another thing that attracted me to CareerFoundry: knowing that I’d come out of the program with something to show for it. And I know that my portfolio was something that impressed my employer during the interview process.

A quote from data analytics graduate Nick about his career change journey

That’s a nice segue to the job hunt! How was your experience in the job search process as you started to look for roles as a data analyst? 

I started the job hunt early—maybe a month or so before I unlocked the Job Preparation Course (which students can begin after completing 51% of their program). So, I kind of had a barometer going into it.

The work I did with my career specialist in job prep made a huge difference in the caliber of my resumé and the whole job application package. For example, having a website for my portfolio—instead of just using a link to a Google Drive folder with my work in it. It just made my whole application package look so much better.

What was your relationship like with your career specialist?

He was super helpful. I don’t think there was a single thing that I turned in to him that he didn’t give back with feedback on how to improve it, which was somewhat frustrating—but at the same time really helpful because he wasn’t just trying to move me on to the next task, there was always really constructive feedback to go along with it. 

So I didn’t make it through the process as quickly as I thought it would, but it was worth it because the end result was a lot stronger thanks to all the work I put in to make my application package stronger.

You’re now working as a data analyst at insurance company, Lockton, which is awesome! How did you come across the company and land an interview?

I think that the main reason I got a job is probably because I did a little bit of networking and I reconnected with somebody that I used to know. I sought him out because I saw from his LinkedIn profile that he was a data analyst and he was working at Lockton, which I knew was a great company. So we got together, chatted and caught up, and that was that. 

Afterwards, I didn’t hear from him for a while and then, a couple of months later, he contacted me and said, ‘Hey, I saw we have this job opening, and I think it’s a really good fit for you. I think you should apply, and I will be your referral for it.’ That was huge! 

Networking was something I was not super excited to do. At least for me, it felt like a chore. Also, I didn’t know if I wanted to get a job because I knew someone; I wanted to get a job because I worked hard for it. But something you have to realize is that networking is going to be a leg up. If you can find a connection, there’s no reason not to pursue it. 

Definitely. Networking can be daunting at first, but it has so much value—and you never know what doors it may open for you in the future.

Yes, and actually, one thing that comforted me was knowing that my mentor, Kaz, was someone in the field: a data scientist. Building a strong relationship with him has put me in a position where I know I can reach out to him for advice, like asking, ‘Hey, when you were a data analyst, what were the steps that you took to get to the next level?’ for example.

A quote from data analytics graduate Nick about his career change journey

That’s good to hear. So, you networked like a pro and landed the interview at Lockton. What was the hiring process like?

My first interview was with my now-boss, and that was actually the most laid-back interview. Now that I’m here (and I’m on the other side of the hiring process), I know that his job in the interview process is to get a general feel for the person, and to figure out if they are going to be a good fit for the team. He does try and gauge if they have some of the technical background needed for the role, but doesn’t hone in on that too much. It’s almost like he tries to get a gut check on every candidate. So I guess I passed that! 

After that, I had an interview with the whole team. It was a panel of four people which, at that point, I thought was going to be an informal interview, but it actually turned out to be the hardest one of them all! Luckily, I was prepared for it. It involved a lot of traditional interview questions, asking what I would do in certain situations, for example. It was all specific to the role, but they were pretty hard questions.

Did you feel like CareerFoundry helped there, knowing you could confidently talk about Python or SQL, for example, or whatever the technical skill or tool might be?

Yes, definitely. Being able to intelligently talk about some of the tools that I worked on thanks to CareerFoundry is not something I would have been able to do before, even though SQL and Python were a couple of things that I’d spent some time on independently before. My understanding of how to apply those in a data analysis setting was what I was lacking. 

A message from CareerFoundry graduate Nick about securing his first job as a data analyst

After the team interview, I was emailed a task to complete at home. That gave me the opportunity to show off many things I learned in the CareerFoundry program.

Thanks for the insight, Nick—and congratulations on landing the job! Could you tell me a bit about your role as a data analyst?

One of the things that I am most excited about with my role is that I get to spend a decent amount of time not only working on the whole data analysis process independently, but also presenting the findings both internally and sometimes in client meetings as well. That was something that attracted me to data analysis: knowing that there is a bit of a hybrid between having a technical role, but also getting to be people-facing and discussing the technical output. I’ve really enjoyed the balance of that so far at Lockton. 

I’ve also had some cool opportunities to explore some of the new skills I’ve acquired and expand upon those, like trying to build new tools and improve current tools. As a new hire, to be involved in that process has been great.

Have there been any surprises or challenges in the workplace that you’ve noticed as a newcomer to the industry?

One thing that surprised me about working for Lockton—and I’m sure this is true of a lot of companies that aren’t startups—is that there were already pre-built tools and functions. That wasn’t really something that we went over the course—learning that some companies will already have tools in place and built out to speed things up, like the cleaning process, for example. 

So at first I did think, ‘Oh, some of the stuff that I learned how to do, I don’t even have to do myself,’ but that’s only in instances where it’s a regular report that we’re doing often. There’s definitely still opportunities for ad-hoc work to deploy all the skills that I know. I’ve really enjoyed the role so far; I’m learning every day, and that’s all I can ask for!

What would you say is the most rewarding thing about working in data? 

I really like instances where there’s problem-solving involved—particularly when there’s a new tool that needs to be developed to solve that problem, or maybe not even a tool, but an instance where you have to start from scratch to get to the solution. That’s probably the best feeling when you’ve worked on something from start to finish and you can say, ‘Yeah, I did all of that. And I solved that problem!’

Yes, I can only imagine how great of a feeling it is when you’ve achieved the end result after putting in so much effort!

Yeah, it is a great feeling. It’s really fun to have that end result, take it to people in other teams, and show or explain to them what the data is saying. And then those teams will take it on board and say, ‘All right, this is what the data is saying—now here’s what we can do with it.’

Getting to work with subject matter experts who can take your findings to the next level and implement them is great. You get to see the thing that you built take flight, you know? 

Definitely. Do you have any advice for anyone who is thinking about a career in data analytics or taking an online course like you did? 

Yes, I guess I have two different answers for that. The first answer would be to the person who is thinking about a career in data and is unsure about what to do next: definitely at least take the free, short course with CareerFoundry. I thought that that was a good window into a career in data. You learn some quick Excel skills which are invaluable. 

To know Excel—no matter what your role—is important. If you work at a business and you know some of the more intermediate to advanced Excel skills, it’s going to help save you time, and maybe even come up with something that’s going to impress your boss. Excel is a huge tool that is a lot more robust than I knew it to be. 

Secondly, to somebody who has already decided to do an online course like CareerFoundry, or perhaps is already in the program, I would say my biggest advice in terms of landing a job is: don’t be afraid to network or reach out to old connections or people you may have once known. 

At least for me, there was a little bit of pride involved in asking someone else for help. Like I mentioned before, when you know you’re on this job search path, and you’re taking all the right steps, you might want to see it through by yourself. But networking is the easiest way to get a leg up on the search. Or maybe not the easiest, but it has the biggest ROI, I feel. Don’t close yourself off from networking.

Do you have any hopes or goals for your future career? 

I feel like I’ve definitely found a home in the data analytics realm. Further down the line, I’d maybe want to do something more along the data science or data engineering track, which is the natural progression in the field, I feel.

Right now the bulk of what I use is Excel and Power BI, and I don’t get to use as much SQL and Python yet, so to be in a place where I am using more programming language skills would be great. I have liked those opportunities so far in my role where I’ve been able to do things that are a little more on the technical side, so I think data science or engineering would be a good fit.  

Great ambition, I am confident you’ll get there. Thanks for talking with me and sharing your story, Nick. I wish you so much luck with your future career and I’m glad things are working out so well for you now!

Has Nick’s story piqued your interest for a career as a data analyst? Find out if data analytics is a good fit for you with this free, introductory, short course. 

If you’d like to learn more about how to retrain for a career in tech, we recommend speaking with one of our program advisors.

by Alison Ward on 25 July 2022

About the author

Alison Ward

Originally from northern England, Alison’s marketing background ranges from gaming, to sports, to the arts. When she’s not writing about CareerFoundry’s inspiring alumni, she can be found doing yoga, reading a weird book, or exploring new restaurants and cafes around Berlin.