Hi! I'm a seasoned data leader and practitioner with expertise in product analytics and data science, data visualization, data engineering, and consumer and B2B products. Head of Data at Modal Learning and a mentor for aspiring data professionals at Springboard. Interested in education technology, coaching/mentoring, road running, books.

I've built and led high impact teams focused on product analytics at Dropbox (DBX) and Udemy (UDMY). As a product analytics manager at Dropbox, I led the groups focused on growth and core product. At Udemy, I was the first product analytics hire and built the team and the function from scratch. My team partnered with our product team to make data-driven decisions by identifying areas of opportunity and delivering insights about the students and instructors on our marketplace. Many years later, elements of the data infrastructure I developed are still in use.

  • Data Science and Analytics

  • Data Visualization

  • Data and Analytics Engineering

  • A/B Testing

  • Airflow, dbt

  • Python, R

  • SQL, Hive, Presto


    Head of Data
  • Designing and implementing our foundational data infrastructure to support the leveraged use of data across the company and externally
  • Responsible for developing and executing on the data strategy for the business, including our initial metrics framework and defining how teams should use data to make decisions
  • Serving as a reviewer and subject matter expert for curriculum in our data science vertical
  • Tools: Python, R, modern data stack tools (including dbt, BigQuery, Segment, Stitch, Metabase)

    Director, Data Science and Analytics
  • Head of the data science function and responsible for team operations, technical leadership, hiring, performance management
  • I built a high performance team with data scientists embedded in our product and marketing teams
  • My team's scope is broadly focused on driving decision-making across the company through quantitative methods (exploratory analysis, applied statistics, A/B testing, causal inference)
  • Tools: Python, R, Redshift, Airflow, Periscope

    Senior Product Analytics Manager (Growth and Core Product)
  • Hired and managed a team of product analysts embedded in two product groups: Growth and Core Product
  • Rapidly scaled the team by hiring and onboarding five new product analysts in 12 months
  • Developed product analytics prioritization processes in consultation with cross-functional partners
  • Tools: Python, R, Hive

    Senior Manager, Analytics (Product)
  • Established and scaled the product analytics function, and hired/managed a team of data analysts
  • Informed product direction and strategy through quantitative analysis of our student and instructor data
  • Provided guidance, mentorship, and direction to the product analytics team and to the entire analytics team
  • Frequently collaborated with our data infrastructure team to continuously improve data quality to enable higher quality analysis and increase trust in data across the organization
  • Developed processes to standardize experimentation and experiment analysis across the product team
  • Tools: Python, R, Redshift, Hive, Chartio, Tableau, Superset

    Quantitative Analyst (Consumer Product)
  • Worked on product, marketing, and SEO analytics
  • Defined and tracked KPIs for the upper funnel of our consumer business
  • Developed tools to track and monitor upstream SEO performance
  • Partnered with our business intelligence team to improve our marketing channel definitions and attribution model

  • Worked at two economic consulting firms, part of consulting engagements spanning a variety of industries and practice areas
  • Provided extensive technical and analytical guidance to analysts and consultants

  • I studied economics as an undergraduate and graduate student
  • Areas of interest include health economics, economics of education, applied microeconomics, and empirical studies of network effects, such as this paper