McKinsey and Company | Data Scientist [2022-2024]
- Led the development of an AI market review, showcasing advanced competencies in artificial intelligence, machine learning, and digital innovation.
- Pioneered a dynamic pricing strategy using CART algorithm for a major industrial distributor, optimizing customer-level pricing.
- Utilized GenAI tools including LangChain, Azure, and OpenAI API to develop a voice automation application for utility services.
- Played a key role in developing an Agent Software Development Kit for interactive agents using the GenAI backend, enabling more flexible usage and development.
- Conducted comprehensive evaluations of backend features (Azure, AWS, GCP) for speech-to-text, llms, and text-to-speech technologies, significantly enhancing app functionality.
- Developed a comprehensive digital twin simulation for a global payments company, aligning parameters with real-world scenarios.
- Demonstrated leadership in AI-based solutions and client management, delivering high-quality results and client satisfaction.
- Created a customer-centric predictive pricing model, managing large and messy data sources, and aimed at robust performance for 1-2 years.
- Spearheaded code error reduction efforts, enhancing program sustainability and readiness for production.
- Transferred models to new data scientists with clear documentation, detailed walkthroughs, and client context, ensuring seamless knowledge transfer.
Numer.ai | Data Science Competitor [2022]
- Compete in a distributed quantitative hedge fund competition using machine learning to predict the performance of anonymized global equities
- Used a XGBoost model with custom training loops and unique time-series based predictors to develop a competitive model and consistently improve in competition ranking and returns
Massive Data Institute | Research Analyst [2022]
- Used Docker to parallelize large scale web-scraping reducing run time by 83% and failed runs by ~66%
- Recognized and engineered 3 new features using Python and React improving user experience and post-run analysis
- Enhanced previous research on public education using web-scraping and NLP to highlight demographic disparities
NASA JPL | Geospatial Data Scientist [2021]
- Researched and developed 6 models to predict Ozone levels from earth observation data using python and Scikit learn
- Utilized back trajectory models for particulate matter integrating HYSPLIT, meteorological data, and earth observations resulting in unique research insights which served as a guide for the 10 week project
- Collaborated to deliver a software product to automate NASA satellite data visualization and analysis
Globally Unified Air Quality (GUAQ) | Lead Startup Data Scientist [2020]
- Designed and carried out comprehensive quality assurance tests to ensure GUAQ monitors ability to perform at industry grade accuracy levels under all conditions
- Developed and implemented an algorithm to transform raw data into AQI metrics for GUAQ’s consumer app
- Ran analysis using machine learning techniques in R to identify anomalies within GAUQ devices data streams
- Uncovered data reliability issues and implemented algorithmic adjustments to increase precision and accuracy of data
Georgetown Entrepreneurship | Operations Analyst [2019]
- Lead the reimagination of the Georgetown Venture Lab as it pivots to an accelerator model, driven by insights from customer interviews, in-depth market analysis, and analysis of comparable programs
- Optimized the Venture Lab by increasing the number desks within the space from 85 to 106 resulting in a $5,250 increase in the monthly revenue ceiling
- Designed and implemented an undergraduate internship program matching 21 interns with 9 companies
EDUCATION
Georgetown University
- Bachelor of Science in Operations and Information Management and Statistics