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Research, Data Science, and Analytics Professional
I am a Research, Data Science & Analytics Leader with over a decade of experience turning complex data into strategic insights that drive meaningful impact. With a background in public policy and statistics, I bring a unique perspective to the challenges at the intersection of government, corporations, technology, AI, and research. My expertise spans education, technology, philanthropy, and policy, where I have built and led high-performing data and research teams, developed novel research, and deployed machine learning to inform decision-making.
At Panorama Education, I led efforts to integrate AI and machine learning into the EdTech space, ensuring privacy-conscious applications of large language models while analyzing student data on academic performance, attendance, and socio-emotional learning. Previously at Fluxx Labs, I focused on predictive modeling in philanthropy, helping organizations make data-driven funding decisions. At Airbnb, I led global data research initiatives that shaped policy decisions in the home-sharing sector. Throughout my career, I have worked to bridge data science with real-world impact, using research and analytics to tackle complex challenges.
I have authored multiple white papers and evaluation reports, including work at the NYC Department of Education, where I provided critical insights into educational interventions and technology use. I am passionate about public service and responsible AI development, ensuring that data is leveraged ethically and effectively to solve pressing societal challenges.
Finally, I think it’s important to have fun. Too much in this world, especially now, already leads to misery. As a leader, I try to make sure my teams are great because they are inspired to great work, not because they were scared into doing great work. I want my colleagues to know we produce serious results but in a way that is approachable and, as much as reasonably possible with statistics, fun.
Lead a team of data scientists at an edtech company, managing large-scale structured and unstructured datasets covering millions of students. Designed and optimized ETL pipelines for analytics and product development, defining KPIs and interactive dashboards to drive strategic decision-making. Conducted advanced statistical modeling and causal inference to analyze academic performance, attendance patterns, and socio-emotional learning trends.
Built and led the data science function at a philanthropy-focused SaaS company, developing machine learning models (NLP, sentiment analysis, and clustering algorithms) to predict grant-making behavior and optimize customer engagement. Designed data warehousing solutions and built scalable cloud-based data pipelines (AWS, Snowflake) to streamline reporting. Led A/B testing and experimentation using tools like Amplitude and Mixpanel, applying modeling to drive product insights. Developed self-serve BI tools in Tableau and Data Studio empowering teams with real-time analytics.
Led a global team of six analysts providing data-driven insights for Airbnb’s policy and regulatory teams worldwide. Designed and implemented automated data pipelines in Airflow and SQL, enabling real-time tracking of regulatory and market impact. Applied causal inference techniques to assess policy effectiveness and economic impact, producing data storytelling dashboards in Tableau for key stakeholders. Built forecasting models to predict regulatory shifts and home-sharing trends, strengthening Airbnb’s data-informed approach to global policymaking.
Transformed the company’s data infrastructure and analytics operations, tripling reporting capacity and modernizing customer-facing research. Led large-scale predictive analytics projects assessing student learning outcomes using R. Developed data pipelines in SQL, automating reporting workflows and delivering actionable insights to product and marketing teams. Created dashboard solutions to track customer engagement and cohort retention, improving data accessibility for cross-functional teams.
Supervised a team of researchers conducting policy-impacting evaluations on student performance and program effectiveness. Designed and executed multi-year studies on education technology, intervention programs, and student engagement using regression modeling, clustering algorithms, and geospatial analysis. Negotiated data-sharing agreements with legal teams and external researchers to establish privacy-first data governance frameworks. Developed custom analytical solutions in R and Python to measure the impact of citywide education policies on diverse student populations.
I love music — check out my mixes and playlists.
NYU Wagner
Master of Public Administration, Policy Analysis
Relevant Coursework: Clustering and Classification; Estimating Impacts in Policy Research; Program Analysis & Evaluation; Applied Statistics in Large Education Databases; World Communication: Principles, Politics & Law.
Tutor for Multiple Regressions and Intro to Econometrics.
NYU College of Arts and Sciences
Bachelor of Arts, Psychology and Sociology with Honors
