About Me

Background

I'm an independent statistician and data scientist specializing in marketing science. My work focuses on helping businesses of all sizes make better marketing decisions through rigorous statistical analysis and experimental design.

Expertise

My approach combines academic rigor with practical business impact. I specialize in:

• Statistical Modeling: Bayesian inference, time series analysis, and predictive modeling
• Causal Inference: Understanding true incrementality and lift through experimental and quasi-experimental methods
• Marketing Mix Modeling (MMM): Quantifying channel contribution and optimizing budget allocation
• Cross-Platform Attribution: Multi-touch attribution and unified measurement frameworks
• Experimentation: A/B testing, holdout tests, and geo experiments

Philosophy

Too many marketing decisions are made based on incomplete data or misleading metrics. Last-click attribution credits the wrong channels. Correlation is mistaken for causation. Experiments aren't properly designed or analyzed.

My mission is to bring scientific rigor to marketing measurement. This means asking better questions, designing proper experiments, using appropriate statistical methods, and being honest about uncertainty.

How I Work

I work with businesses across industries and stages—from startups optimizing their first paid campaigns to established companies managing multi-million dollar budgets. My engagements typically include:

• Initial audit and measurement framework assessment
• Strategy development and experiment design
• Implementation support and analysis
• Ongoing optimization and reporting

Let's Work Together

If you're looking for a data-driven approach to marketing optimization, I'd love to hear about your challenges.