Worked on the News Feed Ranking team, identifying weaknesses in our ranking systems and algorithms, suggesting changes to improve metrics of interest.Serviced, maintained and expanded functionality of our internal engineering tools, helping data scientists on our team identify under-performing segments of our ranking model.Worked with software engineers to push ranking changes to production, and flagged issues with existing ranking configurations.Applied machine learning and predictive modeling to huge datasets and worked with colleagues to identify key-levers for product growth.Built data-pipelines for internal team use and built dashboards that helped visualize key metrics to monitor.

Analyzed the performance of an internal product tasked with amplifying the growth of Facebook Job Ads.Built a machine learning based theoretical framework that shaped the team’s understanding of our product.Determined the team’s top-line revenue impact we should expect from following my recommendations.Collaborated with engineers and designers on my team to build out proposed product changes.

Created and graded coursework, ranging from SQL to deep learning networks.Held hours to help students debug their programs and understand the underlying concepts.

Built machine learning models to evaluate the performance of Facebook’s payments integrity human reviewers.Built data pipelines and corresponding dashboards that allowed the team to automate my analysis.

Built software that leverages the Bloomberg Python API to automate the creation of the bank's forward-facing prospectus documents marketed to other financial institutions.Analyzed supranational bonds across the Latin American region to identify opportunities for future capital raises, in an effort to reduce the bank's cost of debt.