Parul Laul Jordon

Data Scientist/Machine Learning Engineer

Experience

November 2019 - August 2024 WeightWatchers International, Data Scientist III / Machine Learning Engineer

Designed, developed, and maintained an API via the FastAPI framework, that allows WW members to input any recipe URL and receive an estimated WW point value. This utilized OpenAI’s GPT models to parse ingredients and a FAISS-based embedding database for efficient ingredient matching to WW data.

Built and managed a Retrieval-Augmented-Generation (RAG) LLM-based chatbot using LangChain, to enable WW members to access recipe suggestions and nutritional information seamlessly within the WW ecosystem.

Developed a predictive search feature that leveraged member food tracking history and popular brand/restaurant data to anticipate user queries in real-time, employing query expansion methods. Stored top food items in a Postgres database and implemented an API layer on top of the predictive model.

Enhanced and maintained the team’s infrastructure by resolving failed CI/CD pipelines, integrating a debugging tool, and developing a Streamlit dashboard app to monitor build time and sizes. Additionally, supported the migration of products from GCP to AWS, facilitating seamless integration without any downtime.


January 2018 - February 2019 Vituity, Data Scientist

Developed an unsupervised learning model that groups US hospitals based on size, location, and composition, allowing medical directors to appropriately benchmark performance.

Created a predictive model to determine the likelihood of ER patients requiring ICU admission, aiding physicians in triage decisions and optimizing the allocation of rooms and beds.


August 2013 - August 2017 Bronx Community College, City University of New York, Assistant Professor, Mathematics

Published research in quantifying energy loss by light near a rotating black hole.

Taught various undergraduate level courses, such as Linear Algebra and Probability and Statistics.

Supervised undergraduate research projects on general relativity and digital signal processing.


August 2012 - August 2013 Drexel University, Visiting Assistant Professor

Taught advanced undergraduate level courses, including Partial Differential Equations and Linear Algebra.

Collaborated on projects that characterized light paths near rotating black holes.


September 2011 - June 2012 University of Cambridge, Postdoctoral Fellow

Published results on light wave dispersion outside of non-rotating black holes.

Studied mathematical systems related to general relativity with an emphasis on theoretical analysis of black holes.

Technical skills

Education

University of North Carolina, Chapel Hill PhD, Mathematics

University of Toronto MSc, Mathematics

University of Toronto BSc, Mathematics and Biochemistry

Projects

2016 - 2019 Team Chemistry Analyzer for NBA

Used statistical learning to assess how well a random group of NBA players will play together. This was done by building an NBA play simulator using player position data.