I lead the Research Science function for Circana's Checkout consumer receipt panel. Our team is responsible for designing and maintaining the adjustments and methodologies we apply to receipts captured from over 150,000 monthly participant consumers to ensure the most accurate representation of consumer behaviors.

I lead the Research Science function for The NPD Group's Checkout consumer receipt panel. Our team is responsible for designing and maintaining the adjustments and methodologies we apply to receipts captured from over 130,000 monthly participant consumers.

Courses: -Undergraduate Statistics for Political Scientists-Undergraduate Game Theory for Social Scientists-Graduate Statistics for Political ScientistsAwards:Excellence in Teaching Assistantship (2011)

I manage a university-wide, high-impact data analysis and quantitative research team. We provide instruction, consultation, and research collaboration services to a range of users at a world class university: http://statlab.yale.eduOur technical and communication skills stay sharp as we move from helping new learners get started with data analysis to advanced researchers explore complex topics.On any given day, I may meet with a medical researcher to discuss a Bayesian technique for validating their diagnostic questionnaire, help a graduate student optimize their code, update our instructional materials on machine learning in R, enhance our internal reporting pipeline to track service use, suggest some teaching strategies to a graduate student instructor, and plan the allocation of our teams resources for the next year.

Managed design, development, and execution of custom statistical methodologies in support of clients to:- identify advertising/innovation/intervention impact in various scenarios across industries- project unmeasured market sales in various scenarios across industries- quantify consumer responsiveness to marketplace environments- characterize sales response to pricing and identify optimal pricing strategies- forecast market sales into the future as consumer behavior and drivers changeServed as main analytic contact and developer for key projects with Fortune 500 retailers and manufacturers.Managed and mentored junior analysts.Methodologies include predictive modeling (various ML techniques, CV, lasso), causal inference techniques (matching, re-weighting, and regression-based adjustments), multi-stage choice modeling

Visualizing Data (POL 245) at the Freshmen Scholars InstituteDevelop and instruct a new undergraduate course introducing applied statistics with R which covers:- identification of causal effects- clustering of data- prediction and forecasting- analysis of text data- analysis of network data- analysis of geographical dataMost highly rated introductory applied statistics course among students.

Provide consultative support to students and faculty on research projects covering:- data acquisition for structured and un-structured data (e.g., manipulating structured data, scraping web content)- understanding and estimation of standard and bespoke statistical models- setup/understanding of/use of various computing tools (e.g., R, Python, C++, HPC cluster-based tools)