From Microbiology to Data Science: Ryan Larsen’s Transformative Career Journey

Ryan’s journey from microbiologist to Data Analyst at Bidfood New Zealand is a wonderful tale of personal and professional development.

With a solid background in microbiology from Massey University, Ryan had always been drawn to fields requiring meticulous attention to detail, whether through his work in labs or his passion for photography.

Ryan’s interest in data science was sparked by his experience using data to drive improvements while working as an auditor in a factory.

To support his career transition, he enrolled in the Institute of Data’s Data Science & AI Programme.

Ryan’s story exemplifies how targeted education, strategic thinking, and career support can unlock new and rewarding professional opportunities.

1. Ryan, can you tell me a bit about yourself?

I have a background in microbiology. I studied at Massey University. 

Outside of work, I enjoy photography. I have a Canon 7D, and the Canon lens produces beautiful photographs.

I shoot in manual mode, so I need to adjust settings like shutter speed and aperture to get the right shot. There are a lot of details involved in that process. I also enjoy macro photography, which involves close-up shots and requires a lot of attention to detail. I like to take close-up photos of everyday objects that aren’t easily visible to the naked eye.

I’m certainly drawn to activities that require attention to detail, whether it’s photography, microbiology, or data science. Each of these fields demands precision, and problem-solving and attention to detail are integral to all of them.

2. How did you first become interested in data science?

My interest in data science began while working as a microbiologist and later as an auditor in a factory. I collected and then used data to help drive business decisions and improve processes.

Food safety was crucial in the factory, and I dealt with issues like non-conformances daily. I realised that the existing systems, which involved recording data on Word documents and sending lengthy reports, weren’t effective, so I asked myself how these processes could be improved.

I initiated a project to address this gap by developing an auditing system that mapped processes across six or seven departments.

This system produced a graphical dashboard that tracked non-conformances and foreign object findings, among other metrics.

This project allowed me to use data to provide actionable insights, which helped the business more effectively address and prevent recurring issues.

It was really gratifying to see how my work directly contributed to efficiency, reducing non-conformances and saving costs – that is how I first became interested in data science.

3. Why did you decide to study data science rather than staying in your previous field and continuing with what you were doing?

I reached a point in my career where things felt stagnant. I wasn’t seeing any growth or development and I realised I needed a change. 

I thought about advancing my knowledge in the food industry, but it didn’t seem worth the investment.

Then, I remembered a former colleague who completed a Google Data Analytics Certification and landed a job as a data analyst. I decided to give it a shot since I was really interested in data science and keen to move away from my current field.

The course covered fundamental concepts that were useful for starting a career in data science. It took me about six months to complete.

The more I learned, the more I realised how much more engaging data science is than microbiology.

4. How did you come to the decision to study Data Science & AI with the Institute of Data?

I figured that just having that basic Google Data Analytics Certificate might not be enough for me to land a job, especially with the current market competition.

I decided that I needed something more substantial to stand out from the competition.

I didn’t want to spend three years in a postgraduate programme when I could potentially become an analyst in six months.

The Institute of Data’s Data Science & AI Programme had a shorter timeframe—three months full-time or six months part-time—plus the flexibility to work while studying.

5. What was your experience of the programme?

It was a steep learning curve, but I was passionate and willing to learn, so it was a great experience overall.

Since I had never learned Python before, and the Google Data Analytics certificate didn’t cover It, I found learning it to be a significant challenge.

Focusing specifically on Python for data science rather than broader programming topics helped me channel my learning and make the Python I did learn more relevant to data science. Concentrating on the various tools and packages within Python related to data science—like data cleaning, data science pipelines, and machine learning models—was essential.

The programme had a mix of like-minded people and skilled instructors. Our main trainer was an industry expert, and our tutors helped in the online breakout rooms.

This setup allowed us to discuss problems and review our work on a case-by-case basis, which I found really beneficial.

6. Do you have any advice to help students get through the programme?

First and foremost, persistence is key. Having a willingness to learn will help you succeed.

Ask your tutor to provide or recommend useful books and resources for further research.

Apply what you’ve learned and use your background skills throughout the programme.

If you encounter problems, make sure to reach out for help and use the resources you have available to you.

7. Can you tell me about your capstone project?

The Capstone project was an opportunity to apply my new skills in a practical way. I chose a project that would be useful for my future career rather than just something I enjoyed during the programme.

I worked on a customer churn analysis project, where I predicted whether a customer in the telecommunications industry was likely to leave. I used data cleaning, validation, and machine learning models, achieving about 75% accuracy.

One of the business analysts at the company I now work for asked for advice on potential projects, and I was able to suggest using my customer churn analysis as a model.

8. How did you approach your job search?

Transitioning into a new career as an analyst or data scientist was daunting.

At the forefront of my mind was that I was not only switching jobs but also moving to a completely new field. 

I reached out to the Job Outcomes Team at the Institute of Data for help with my job search. They were particularly useful in supporting me in developing my resume and cover letter to an industry-relevant standard. While most of my resume was already well-constructed, their expertise in tailoring it for a career change was invaluable.

They understood and took into account the specific circumstance I was in of transitioning into the new field of data science. Their assistance was crucial in helping me present my previous experience alongside my new skills effectively.

After this update, I was fortunate to be contacted by a recruiter through LinkedIn, which highlights the importance of maintaining an updated profile.

9. Fantastic news. Can you tell me about your new role?

I am a Data Analyst for the procurement team at Bidfood New Zealand. It is a distribution company with warehouses across the country. 

My current role involves working on a warehouse system project that predicts issues like overstocking or understocking items. This helps optimise inventory and reduce waste. We focused on revolutionising our reporting processes.

Previously, the company used Excel macros, but we aim to transition to more advanced tools. We now utilise Power BI and Python to automate and streamline these processes. 

I also work with an SQL database on a daily basis. SQL skills are critical for analysing and querying databases, filtering data, and understanding dimension and fact tables. Developing Power BI tools and using Python for automation projects were key aspects of my role, though, because these tools help reduce repetitive tasks, minimise human error, and uncover important insights using machine learning models.

10. Do you have any advice for those undergoing the Data Science job hunt process?

Yes, I would pass on the fact that the Institute of Data provides graduates with very useful job outcomes resources.

Be persistent and apply for as many jobs as possible, even if you only meet some of their requirements. 

Show your willingness to learn and adapt. If you find you’re missing some skills, consider how you can acquire them to meet job requirements.

11. Do you have any advice to share with individuals aspiring to enter the data science field?

Having knowledge and understanding of Python, especially for automation in business, is invaluable.

If you’re entering a business where Python is not yet utilised, being able to implement Python processes can be a major selling point. With skills like Python, you can show potential employers or recruiters your use cases and how you can add value with your Python expertise.

12. How do you feel now that you’ve finally entered the data science industry after setting that audacious goal for yourself?

It feels incredible. Changing careers was daunting, but achieving a positive outcome has been very rewarding. Initially, I feared starting over from the bottom, but seeing the results has been gratifying.

13. Is there anything else that you want to share that we haven’t covered today?

The Data Science & AI Programme is fast-paced, but it is taught by professionals, and even if you have a busy schedule or other commitments, you can fit it in. 

If you’re considering taking this programme, think about where you want to be in ten years. With five to ten years of experience, you could become a data scientist and even move overseas.

Having a certification and extensive experience can be very valuable. As I mentioned earlier, you don’t necessarily need to start from scratch; you can leverage your skills and experience to advance in your career.

If you’d like to learn more about our Data Science & AI Programme, please download a course outline.

Alternatively, you can speak about the programme directly with a team member by booking a career consultation to start your journey with an actionable plan.

You can connect with Ryan and follow his professional journey on Linkedin.