Summary
Longhow Lam is an experienced data scientist with 11+ years applying statistical modeling and machine learning across telco, banking, retail and consumer goods, currently focused on forecasting and consultancy from Amstelveen. He combines deep expertise in credit risk and Basel modeling with practical production skills in Python, R, SAS, BigQuery, Databricks and Shiny to deliver CLTV, churn, fraud and demand-forecasting solutions. As a frequent public speaker and coach, he helps teams adopt tools like Dataiku, Snowflake and Azure ML while translating complex models into actionable business insights and visualizations. His background in mathematical modeling and early career work with S-PLUS gives him a rigorous quantitative foundation that he pairs with modern engineering practices. Notably, he bridges academic rigor and hands-on delivery—building everything from computer-vision floor-area extractors to BigQuery ML customer-lifetime platforms—making him a versatile partner for analytics transformations.
11 years of coding experience
16 years of employment as a software developer
MSc. (In dutch doctorandus), Mathematics & Statistics, MSc. (In dutch doctorandus), Mathematics & Statistics at Vrije Universiteit Amsterdam (VU Amsterdam)
Atheneum, Atheneum at Copernicus scholengemeenschap
Post MSc Mathematical modeling, In Dutch: Post doctorale opleiding Wiskundige beheers- en beleidsmodellen, Post MSc Mathematical modeling, In Dutch: Post doctorale opleiding Wiskundige beheers- en beleidsmodellen at Delft University of Technology