Experience
Data Scientist, QuantCo
July 2024 - Present
Build machine learning models and predictive algorithms for various business clients
Run statistical analyses to quantitatively assess business decisions and performance
Data Science Intern, Bridg
October 2023 - May 2024
Created scalable machine learning algorithms and pipelines in Python to analyze terabytes of customer and product data
Generated customer segmentation pipelines via machine learning algorithms to automate audience creation
Researched and assessed large language models to assist with data democratization for internal users and clients
Data Science and Visualization Intern, Apple
June 2023 - September 2023
Extracted insights from user studies via natural language processing with deep learning for topic modeling and sentiment analysis in Python
Analyzed and visualized user study results for Vision Pro using R
Provided product and business insights for use by various teams as a member of the DataViz team (within Hardware Engineering)
Graduate Research Assistant, Stanford University
January 2023 - September 2023
Analyzed randomized controlled trials for energy efficiency and worker incentives for brick kiln owners across South Asia in R
Ran random and fixed effect regression models to assess performance improvements
Standardized, processed, and performed QA survey data in real-time from various questionnaires
Performed statistical analyses and produce various data visualizations to present to the Bangladeshi government
Research assistant for the Luby Lab (under Dr. Stephen Luby)
Data Science Intern, Bridg
June 2022 - November 2022
Constructed machine learning models with AWS Sagemaker (in Python) and Snowflake (SQL) to analyze terabytes of data
Developed natural language processing (NLP) algorithms to standardize and categorize product descriptions for enhanced business analytics
Unified and standardized attributes for millions of profiles from multiple sources through statistical analysis and imputation
Web scraped, visualized, and analyzed correlations between minimum wages and menu prices in various urban areas
Assisted product recommendation and churn identification via machine learning models in Sagemaker and Snowpark (Snowflake Python API)
Data Analyst Intern, SCAN Health Plan
November 2021 – June 2022
Gathered insights about SCAN membership experience challenges by analyzing Voice of the Consumer (VOC) data in Python, R, Tableau, SQL
Analyzed over 1 million member calls with natural language processing (NLP) and unsupervised learning in Python to generate FAQ sections
Visualized benefit categories and disenrollment groups with visualizations in R and Tableau
Queried disenrollment data from SQL, visualized in Tableau and R, analyzed demographic disenrollment rates via chi-square, posthoc analyses
Presented findings, insights, and learnings to leadership teams and in all-teams meetings
Data Science Consultant, UCLA Library Data Science Center
November 2021 – June 2022
Consulted to help researchers curate, transform, analyze, and visualize their data using R, Tableau, Python, SPSS
Performed chi-square analysis, multidimensional KS tests
Reverse geocoded addresses using Google Maps API
Implemented regular expressions to extract highlighted texts and associated questions in Python
Member of the DataSquad, a student-run division of UCLA's Data Science Center
InStep Intern (Data Analytics and AI), Infosys
June 2021 – August 2021
Defined and identified specific patterns of play for analytics for Roland Garros and the Australian Open
Helped the team use machine learning to develop AI commentary for engaging point-by-point descriptions