Curriculum Vitae

Lead Analyst, Experimentation — Personalization, Product Analytics & AI Workflows

Experimentation and data science lead with 6+ years in streaming and e-commerce. Specialize in A/B testing strategy, causal inference, personalization research, and building self-serve analytics tooling. Background in Bayesian modeling, ML productionization, and AI-driven workflow automation.

Experience

Lead Data Analyst, Experimentation — Disney Streaming

Sep 2021 – Present

Remote

  • Owned end-to-end experimentation across personalization, search, programming, and advertising domains including A/B testing automation, pre/post analysis, metrics development, and research
  • Led a research initiative investigating how non-promoted content gets discovered by personalization algorithms, delivering actionable recommendations to cross-functional stakeholders
  • Developed novel experimentation metrics (engagement intent, content novelty, vertical positioning) and made them self-serve for partner teams
  • Built an experimentation capacity planning tool providing automated insight into test slating and resource allocation
  • Demonstrated that broader personalization of content surfacing drove double-digit engagement lifts across all user segments, not just power users
  • Integrated AI-driven workflows leveraging MCP connections between Claude, Jira, Databricks, and Google Drive to accelerate stakeholder insights and operational efficiency

Lead Data Analyst, Data Governance — Disney Streaming

Mar 2021 – Aug 2021

Remote

  • Led team of 2 building API integrations and crawlers to support data governance and compliance

Sr Analyst, Data Instrumentation — Disney Streaming

Jan 2020 – Mar 2021

New York, NY

  • Developed a scalable data quality monitoring framework using PySpark to optimize validation across large-scale datasets
  • Built and maintained Databricks pipelines and Looker dashboards to monitor and communicate data quality health
  • Mapped end-to-end data stack dependencies to support cross-functional initiatives

Statistical Analyst — Dia&Co

Nov 2017 – Sep 2019

New York, NY

  • Built hierarchical Bayesian models and mixed-effects models to estimate product elasticities and measure discount effectiveness with reduced sample sizes
  • Developed a predictive replenishment algorithm that reduced inventory out-of-stock periods
  • Authored data pipelines to compute and monitor KPIs and inventory state changes for merchandise stakeholders

Data Analyst — Flocabulary

Sep 2016 – Aug 2017

Brooklyn, NY

  • Designed and productionized ML models (logistic regression, random forest) for conversion prediction, piped directly into Salesforce for sales team prioritization
  • Built data cleaning and deduplication pipeline with SQL and fuzzy matching, halving dataset size

Research Associate — NYU Tandon School of Engineering

Jun 2016 – Jan 2017

Brooklyn, NY

  • Developed iOS and Node.js applications for the goViral participatory health and citizen science research project
  • Successfully shipped app to the iOS App Store

Academic Research

2005 – 2015
  • Brooklyn College (2013–2015) — Microbiology lab management, protocol development, student instruction, and data analysis
  • University of Delaware (2010–2012) — Collagen mimetic peptide design for gene delivery scaffolds
  • Johns Hopkins University (2008–2010) — Characterization of collagen mimetic peptides; solid-phase peptide synthesis, MALDI, HPLC
  • University of New Mexico / Sandia National Labs (2009) — NSF REU; nanoparticle toxicity, protocell drug delivery, confocal microscopy
  • Columbia University (2005–2007) — TIRF microscopy of calcium dynamics in cell spreading (Sheetz Lab)

Publications

Education

Georgia Institute of Technology

MS, Online Master of Science in Analytics (OMSA) — In Progress

Metis Data Science Bootcamp

Data Science Intensive — 2016

University of Delaware

MMSE, Materials Science and Engineering — 2012

The Johns Hopkins University

BS, Materials Science and Engineering — 2010

Skills

Events & Community