Aastha Chawla

• Developed a predictive response model V2 to identify small businesses likely to apply for No-Preset Spending Limit (NPSL) cards; captured 4000+ new accounts with an estimated $65M in annual spend at an 85% approval rate • Led Targeting and Prioritization (TAP) strategies for the Venture X Business card, Capital One’s flagship travel product, enhancing lead quality and boosting marketing efficiency by 8% through pre-decline filtering • Partnered with marketing, data & business analytics teams to translate model insight into scalable customer acquisition strategies under Business Cards and Payment Division.

Capstone Project at UT Austin in Spring'24 • Implemented a Transformer-based model for generating contextual embeddings and conducted Transfer Learning to fine-tune that pre-trained model for air shop requests. This approach significantly enhanced the predictive capabilities and efficiency of air shopping processes. • Utilized advanced Natural Language Processing (NLP) techniques and Large Language Models (LLMs) to intelligently standardize text data, streamlining operations and improving data quality for 3.5 million+ addresses.

Teaching Assistant for • Spring 2024 - Foundations of Data Analysis, conducting hands-on labs for Predictive analysis, forecasting and time-series modeling. • Fall 2023 - Digital Image Processing, key highlights - Deep learning, perceptrons and neural networks. • Spring 2023 - Foundations of Data Analysis, key highlights - Linear Regression, t-tests, Chi-squared test and ANOVA; managed three undergrad course assistants. • Fall 2022 - Elements of Statistics, key highlights - Descriptive Statistics, Inference and Hypothesis Testing and Regression using R; supervised six undergrad course assistants.

Rebuilt Graduate Student Assembly's website and increased overall online presence for communicating with UT Austin graduate students through our official social media accounts and monthly newsletters.

Graduate Data Science Intern in Customer Growth Marketing Team. • Developed a feature ranking methodology for LightGBM classification model to select top 20% features (1500 out of 8000); improved share of potential customers by 4% and simplified the infrastructure stack without degrading model performance. • Modeled a stacked ML classifier (Base model - XGBoost and Meta model - Logistic Regression) to identify customer's likeliness to buy and designed end-to-end framework in Python with 200M rows in the backend to challenge existing methodology; reduced training time by 10% Member of “Women in Action” - an Employee Resource Group at Dell

Senior Business Analyst in Finance Decision Science & Analytics Team • Led the automation and optimization of Credit Card Member Value model which enhances customer acquisition, lifecycle spending and investment performance. Achieved this by successfully transitioning the process to a production environment, reducing the SLA by 1 week, and removing all manual interventions. Skills Used: Pyspark and SQL. • Awarded "Global Excellence Award in Agility and Innovation" for developing a 99% accurate time-series forecasting ML algorithm and "Star of the Quarter" for ensuring timely delivery, solution-oriented, and collaborative approach in Project Tesla. • Spearheaded cohort segmentation analysis to uncover cross-sell potential and reduce cannibalization across US Consumer and Small Market business units, driving 4% lift in cycle funding Member of FDS - CEAT (Colleague Engagement Activities Team) 2022 where I led Focused Group Discussions, managed Learning and Development sessions and rolled out Rewards and Recognition within the global team.

Data Analyst in Acquisitions and Portfolio Insights team of American Express. • Developed a robust and scalable ARIMA model which automatically forecasts the US acquisition base at a weekly level. These estimated numbers were used by marketing stakeholders to track the performance run-rate of their campaigns. Reduced root-mean-square-error (RMSE) of this time-series model from 8% to 1% by treating outliers at each top channel and performing stationarity tests like Dickey Fuller. • Migrated Acquisitions Database in Big Data Platform using Hive (from SAS) for 25 International markets which have 250+ KPI metrics for meeting the Investment Optimization Plan. • Designed a Tableau-based dashboard with dynamic and quick KPI insights for 25 markets and later, improved the performance by 98%. • Product Owner of Acquisitions Database for 25 markets including Canada, UK, Mexico, Germany, etc which catered to 800+ business stakeholders. Member of Enterprise Digital Analytics (EDA) India Inclusion and Diversity Team 2020 where I led reverse mentoring sessions at global level during the virtual Covid-19 setup. Member of India Finance Inclusion & Diversity Team 2021 where I published newsletters on the Amex Internal webpage about geographical cultural diversities.

Selected in SURGE 2018 program. • Research Project- Designed, Analysed, and Modeled Ultra-Light Lattice Structures using 3D Printing Technique (Selective Laser Melting process) in IIT Kanpur. • Mentored by- Dr. Arvind Kumar, Assistant Professor, Indian Institute of Technology, Kanpur

As the Event Coordinator, I have been actively involved in event management, sponsorship management, marketing and networking. Been the participant and coordinator of the business plan event.

Committee Head of the annual cultural fest at NIT Kurukshetra. Secretary of Spicmacay Club - NIT Kurukshetra Chapter. Awarded by the Faculty President for organizing annual cultural fest of NIT.

Just Another Magazine(JAM) is a student run biannual magazine of NIT that encompasses articles on issues pertaining to the college going generation run by students. As a graphic designer, I have been involved in content designing and layout of magazine along with content creation for some articles.

Courses: Machine Learning, Time Series Forecasting, Linear Programming, Decision Analysis, Statistical Methods, Applied Stochastic Processes, Texas Venture Labs and Applied Probability

Courses: Operations Research, Statistics and Probability, Differential Calculus, Business Management, Engineering Economics