Hi! I'm a seasoned data leader and practitioner with expertise in product analytics and data science, data visualization, data/analytics engineering, and consumer products. Experienced builder of 0 to 1 data systems and infrastructure. Currently the Head of Data at Evernest. Mentor for aspiring data professionals at Springboard. Occasional technology startup investor (primarily in AI, consumer products, space, defense). 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
  • Head of the data function, including data engineering, data science and analytics, and data governance
  • Tools: Python, dbt, BigQuery, Snowflake, SQL Server, Metabase, multi-cloud infrastructure (GCP + Azure)
    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, 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 the growth product and core product groups
  • 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