adrian tame

I am a data scientist with a career spanning market research & consulting, hands-on data science, and data science management. Across these roles, I have focused on building analytical capabilities that translate complex data into actionable insights, while guiding teams to deliver rigorously grounded, business-relevant solutions and purposeful academic insights.

My work centers on advanced statistical and machine learning methods, with particular emphasis on Bayesian optimization, time series forecasting, and causal inference. I specialize in time series analysis, especially financial time series, where I focus on modeling temporal dynamics, uncertainty, and causal effects. I have extensive experience designing and evaluating experiments, including large-scale A/B testing frameworks, and applying rigorous causal methodologies to measure impact in complex, real-world environments.