Interview with Virgil Chan, scikit-learn Team Member

"My name is Virgil, and I'm currently working as a Forward Deployed Engineer - Pre-Sales at Union.ai. Based in San Jose, California, I previously worked as a consultant, using libraries from the scientific Python ecosystem on data science and machine-learning projects, including medical data analysis, traffic-network prediction, and model evaluation. Before deciding that computers are more fun, I was doing mathematical research in topology."

"I first got involved in open source during the COVID-19 lockdown. I used that time to study Python programming, data science, analytics, and machine learning, and that's when I discovered libraries like NumPy, Pandas, scikit-learn, NetworkX, and TensorFlow. Once I became more confident in my skills, I started working as a consultant and used these libraries to deliver data-driven solutions for clients."

Virgil Chan works as a Forward Deployed Engineer - Pre-Sales at Union.ai in San Jose, California. He previously consulted on data science and machine-learning projects using scientific Python libraries for medical data analysis, traffic-network prediction, and model evaluation. He began with mathematical research in topology before moving into computing. The COVID-19 lockdown prompted focused study of Python, data science, and machine learning and led to discovery of NumPy, Pandas, scikit-learn, NetworkX, and TensorFlow. Consulting work provided practical experience and confidence, while the transition from academia highlighted the importance of hands-on experience and open source contributions.

Read at scikit-learn Blog