About Me

I’m a data scientist with 7+ years of experience building ML models and analytics infrastructure, supported by a decade-long analytics background spanning advertising and healthcare research. I’m driven by creating data solutions that enable smarter business decisions

What I Do

I specialize in:

  • Machine Learning: Building predictive models for classification, regression, and propensity scoring using Python and scikit-learn
  • Data Engineering: Designing scalable data pipelines and transformations with SQL, dbt, and cloud data warehouses
  • Analytics & Visualization: Creating actionable insights through Tableau dashboards and statistical analysis
  • Production ML Systems: Deploying models that process hundreds of millions of rows and generate revenue

Background

Most recently, I worked as a Data Scientist at Omnicom Media Group, where I built ML audience segmentation models and automated workflows that reduced model creation time from one week to two hours. Before that, I served as a Business Intelligence Analyst at The Trade Desk, developing analytics infrastructure for client services teams.

I hold an MS in Biostatistics from Columbia University and completed intensive training in data science at Metis. My technical foundation includes Python, SQL, machine learning, and modern data stack tools like dbt.

Current Focus

I’m passionate about building production-ready data systems and exploring the intersection of data science and analytics engineering. Currently, I’m working on projects that demonstrate modern data engineering practices and anomaly detection techniques.

When I’m not working with data, I enjoy spending time with my family, fixing up our new house, and doing various crafts.

Last updated: February 2026