Global Quantitative Strategies (GQS).

- Managed a research collaboration with a large insurance company, including the extract, transfer, and load of large observational datasets, development and maintenance of software packages, and planning and organization of weekly and quarterly meetings.- Developed novel algorithms to identify heterogeneity in decision-making processes, and applied them on real-world healthcare datasets to study variation in treatment patterns in collaboration with physicians and other stakeholders.

TA for Introduction to Machine Learning (6.036). Ran 4 weekly recitation sections with around 10 students each, in addition to regular open office hours. Averaged a rating of 6.7/7.0 (6.6, 6.8, 6.8) on student evaluations.

- Built predictive models for some futures symbols using linear and ensemble models.- Built predictive models for short-term lead-lag relationships between fragments of U.S. equity markets.

Modeled short-term interest rates in several countries using macroeconomic indicators.

Built gene-tools, a Python tool for deterministic and reliable protein-gene mapping across multiple gene nomenclatures. Integrated into Genoppi, a software package for robust integration of proteomic and genetic data.