Most tech careers aren’t linear—and yours doesn’t have to be either. Dr. Jason Bernard shares his unconventional journey from programming video games at age 11 to pioneering AI algorithms that could revolutionize biotech and urban planning.

In this eye-opening episode, Jason reveals how his diverse experiences—from military service to music composition—fuel groundbreaking research in process modeling and data science. You'll discover:

How early programming and limited hardware shaped his approach to elegant, resource-efficient algorithms

The real difference between machine learning, AI, and data analytics—and why understanding this distinction is key to future-proof skills

The fascinating world of modeling biological processes, like gene-expression for drought-resistant crops, using reverse engineering in data science

Why simplicity and human insight remain essential in an era dominated by neural networks and language models The future of data science careers in a rapidly evolving tech landscape and practical advice for new professionals

This episode is perfect for tech enthusiasts, data scientists, and students eager to learn how a curious mind can make an impact across industries—from agriculture to telecommunications—and why adaptability and a deep understanding of algorithms are the secret weapons for success. With over 18 years of research and real-world experience, Jason is an assistant professor at Athabasca University, known for pushing the boundaries of process modeling and optimization. His work on inferring computational models from real data has been called the “holy grail” by leading experts. If you're looking for inspiration on how to navigate a non-traditional tech path or want to understand the core principles behind cutting-edge AI research—this episode will change the way you see your career.

Hit play and unlock your potential today.

Host Kevin Evans