Education:
Rutgers University – New Brunswick (2020-2024)
• Bachelors of Arts in Computer Science
• Bachelors of Arts in Economics
Relevant Coursework
Computer Science
Intermediate Macroeconomics, Intermediate Microeconomics, International Economics,
Economic Forecasting and Big Data, Financial Economics, Advanced Time Series
Economics
Econometrics, Intermediate Macroeconomics, Intermediate Microeconomics, International Economics, Economic Forecasting and Big Data, Financial Economics, Advanced Time Series
Professional Experience
siParadigm Diagnostic Informatics ~ System Analyst
Jun 2025-Present
● Coordinated the creation of an AI-powered development ecosystem, integrating Cursor and Windsurf tools to streamline workflows and increase productivity by more than 100% for MVP creation.
● Deployed standardized three SRS, URD, and BRD templates for new AI-driven Agile/Scrum frameworks; improving stakeholder alignment for over 15 stakeholders within the Jira platform.
● Engineered React code for Client Portal using Windsurf, spearheading a significant platform revamp that boosted UI/UX usability scores 20% and slashed E-requisition processing time by over 3 hours weekly.
● Spearheaded the creation and business analysis of the company’s new KPI portal visualizing 5 critical indicators and transmuting sheet data to web application lowering KPI report generation by over 20%
Intelligent Applications (IntelApps) – Product QA Analyst Intern
● Collaborated with global stakeholders to develop over 40 detailed test cases for enterprise invoicing system, utilizing Excel to track defects and improve software quality assurance processes.
● Executed performance benchmarking across application layers for pharmaceutical distribution systems, decreasing processing time by 15% and improving overall system efficiency.
● Conducted thorough QA analysis on the student application platform, leveraging test cases that improved application performance by over 5% and reduced critical bugs pre-release by over 5%.
Projects
Bitcoin Quantitative Machine Learning
● Leveraged Random Forest Regression and Seaborn libraries to produce impactful data visualizations from Bitcoin data,
identifying three key factors influencing volatility and macroeconomic policy based on treasury yields.
● Produced data visualizations using Python Matplotlib, Seaborn libraries, and Python programming, generating statistical
indicators including R-squared error of 0.96 and successful back-testing.
● Integrated financial data into a SQL database using SQLAlchemy, optimized query performance, and reduced average
data retrieval time by 30%, enhancing efficiency for downstream data analysis tasks.
Tax Lien Data Scraping
● Developed a data scraping tool in Python from website HTML for property record and tax lien information, extracting
sale information across all 21 New Jersey counties.
● Applied LXML for data parsing to extract and process HTML table information, generating readable outputs that
provided insights into housing sales totaling over $800,000.
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