About me

Hi! I am a rising senior at Northwestern University double majoring in Computer Science and Data Science. I love taking complex technical problems / tools and shaping them into clear, accessible solutions for people to use.

My combined background provides a holistic understanding of the technical challenges I tackle. Because I have hands-on experience across the entire lifecycle of a product, from architecting data pipelines and training predictive models to developing dynamic front-end interfaces, I can see the complete picture. This visibility allows me to bridge the gap between raw logic and the final user experience, enabling me to engineer resilient, integrated platforms that provides value to any user.

Core Skills

  • Software Development

    Building full-stack web applications, design/implement dynamic frontend components, and robust backend from the ground up.

  • AI & Machine Learning

    Integrating LLM agents and predictive modeling frameworks to automate research, parsing, and complex system logic.

  • Data Engineering & Analytics

    Architecting scalable data ingestion pipelines and centralizing complex datasets to power dynamic dashboards/data reports, uncover trends, and drive decision-making.

Resume

Education

  1. Northwestern University

    2023 — 2027

    Bachelor of Arts in Data Science | Bachelor of Arts in Computer Science
    Cumulative GPA: 3.99/4.00 | Major GPA: 4.00/4.00 | Dean's List: 9/9 quarters

Experience

  1. Software Engineer — MyFlexLearning

    March 2026 — Present
    • Engineered a large-scale constraint satisfaction scheduling engine utilizing Google OR-Tools, processing complex custom requirements to generate comprehensive school schedules.
    • Integrated OpenAI API to parse natural language inputs into structured database configurations, utilizing strict prompt engineering and data validation to guarantee data accuracy and integrity.
    • Designed dynamic backend pipelines to parse JSON constraint parameters into the solver, optimizing computational efficiency via advanced data pruning and precalculation algorithms.
    • Developed 3 dynamic front-end components from scratch using Angular, TypeScript, and HTML, resolving asynchronous race conditions to ensure seamless state management and UI rendering.
    • Performed end-to-end testing on the scheduling feature, identifying and resolving 20+ logical, functional, and display bugs.

  2. Research Associate — Northwestern University/Open Communities

    November 2025 — March 2026
    • Architected a fully containerized Python web application using FastAPI deployed on Railway, automating fair housing analysis across peer modeling and lender profiles.
    • Built centralized data ingestion pipelines utilizing U.S. Census and FDIC APIs, applying Scikit-learn and SciPy to execute predictive machine learning and statistical modeling.
    • Collaborated with stakeholders across varying levels of technical expertise, translating complex analytical concepts into clear, accessible explanations to support informed decision-making.

  3. Data Engineering Intern — Continental Tires

    June 2025 — August 2025
    • Analyzed and modeled attendance data for 2,000+ employees, identifying workforce trends, uncovering anomalies, and creating visual reports to support HR planning.
    • Designed and deployed Power BI dashboard with SQL Server integration, providing real-time electricity consumption data and historical usage trends to aid energy management.
    • Developed Python pipelines to automate data collection and aggregation from multiple manufacturing platforms and file formats, eliminating manual reporting and visualizing operational trends for decision-making.

  4. Data Engineer — MyFlexLearning

    June 2024 — May 2025
    • Engineered pipelines for a customer-facing data report card and 3 internal data reports using Python and SQL to aggregate customer configurations, delivering actionable system usage insights utilized by 100+ K-12 schools in the US and Canada.[cite: 1]
    • Created scripts and workflows that interact with multiple APIs, handling data essential to the platform's core functionality as well as datasets used for system usage analysis and reporting.[cite: 1]