Luiz Leveraged His Domain Knowledge and Upskilled to Data Science & AI in 24 Weeks

From healthcare and insurance to data science and AI

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With more than 10 years of industry experience in healthcare and insurance, Luiz Carneiro had a passion to create change and resolve complex issues so he gained relevant practical data science, data analytics, machine learning, and artificial intelligence skills to accelerate his career path.

In just 6 months Luiz re-trained and graduated from the Institute of Data’s Data Science and AI Part-time program at the University of Technology Sydney – he now works for Aginic as a Data Science Lead – allowing him to combine his existing domain knowledge and new data skills to pursue a long term career in the rapidly growing data industry. This is his journey so far:


What was your career experience before making the change to data science & AI?

“My background is in economics and actuarial science. I did a masters in economics in Brazil, and I have a PhD in actuarial studies from UNSW. I am a fully qualified actuary with more than ten years of experience in consulting within different lines of insurance and healthcare. Most of the consulting work I have done involved data. I have also taught actuarial science at the University of Sao Paulo and led a private think tank in private health insurance.

Before joining Aginic, I worked for Roche Diagnostics in Brazil, in a global project to optimise cancer care pathways.”

Having experience in the Healthcare industry, how did you transfer and apply those experiences to prepare you to study data science?

“Healthcare is a very complex sector, with many data-related problems. So, my experience in healthcare helped me understand the data problems that could be solved with data science. What helped me to study data science was my background in mathematics and statistics, as well as my previous experience with data-related consulting projects.”

What were your career goals before upskilling to data science?

“My career has always been related to data in some way, but data science enables you to solve data problems with more powerful tools. I am looking forward to pursuing a long term career around this profession.”

Why did you choose to join the Part-Time Program in particular?

“I chose the part-time program because I was also working. What appealed to me was the quality of the lead trainer (Amin Khatami) who was able to go deep into the content so my classmates and I could better understand the theoretical and practical aspects of data science.”

You’re now working as a Data Science Lead with Aginic – Congratulations! What guidance would you give someone applying for jobs after upskilling / preparing for a data science interview?

“There is no golden recipe. I believe that good connections and networking are extremely important and you should understand the employer’s business, objectives and major problems. It is also important to have relevant projects to show to prospective employers, so you can demonstrate your practical skills.”

What surprised you the most about your new job?

“The diversity and quality of the people who work at Aginic. The collaborative culture within the company is an aspect I really value.”

How do you compare your career outlook now to 6-12 months ago?

“I feel more excited because after upskilling I have the potential to solve a lot of relevant problems with data science!”

What do you know now that you wish you knew before changing careers to data?

“What I know now is that developing a sound knowledge in data science can make a big difference in terms of professional opportunities. It also gives you the ability to continue learning and improving. Another thing that data scientists should be aware of is that they will always work with multidisciplinary teams. Understanding the customer’s needs and objectives is crucial, so data scientists also need to communicate well and work well within groups.”

Tell us about your capstone project! How did you come up with your topic?

“First, I had to decide between insurance and healthcare, which are my two areas of expertise. I decided to go with healthcare because of good contacts in Brazil’s healthcare industry, who could provide me with high-quality data. I was lucky enough to have access to a real data set from more than 140 acute care hospitals in Brazil. With that data, I was able to come up with relevant models to predict the length of stay for cardiac disease patients.”

Now that you’re trained with in-demand skills and working in the industry, what’s your future career plan / what processes do you hope to experiment with going forward in your data career?

“My career plan will be to help businesses to achieve what they want and solve their problems with data science. I want to keep learning and applying new tools and techniques. I am especially interested in NLP and deep learning.”

What advice would you give a professional that wants to kick-start their career in an industry that’s new to them?

“I believe it is important to identify transferable skills. In my case, for example, previous consulting experience in data projects and a sound background in maths and statistics helped me a lot. Think about how you could use your previous knowledge or skills to help make a career change.”

You’re also working as an Assistant Trainer with the Institute of Data! How is the experience of teaching data science after upskilling?

“The experience has been great. You learn a lot when you teach and I have also been able to learn a lot from Ahmed Fattah, the Lead Trainer, and from the students, who work hard and always ask questions to inform their learning in our hands-on class environment.”

Read more: Strategies for learning skills in Data Science and AI by Ahmed Fattah.

Connect with Luiz on LinkedIn here.

If you are interested in up-skilling and transitioning your career to the Data Science field, schedule a consultation with a Data Industry Career Consultant today.

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