Data engineer and analyst with 3 years of experience building production pipelines, AI-powered platforms, and data governance systems across finance, healthcare, and labor markets.
Data AnalysisPythonSQLData VisualizationPower BIPostgreSQLBigQuerySnowflakeA/B Testing
Selected projects
Career Compass | Labor Market Analytics Platform
• Built an AI-powered labor market analytics platform processing 3M+ records, combining LLM-assisted querying, interactive visualizations, and career intelligence to support data-driven advising. • Research paper accepted (forthcoming): SET III Symposium on Entrepreneurship & Technology, 2026.
• Won 1st place at BU MET Hackathon 2025 by building a sentiment-driven trading strategy with automated backtesting and an interactive portfolio performance dashboard.
• Predicted dispute outcomes and automated intent detection across thousands of consumer complaints using a Naive Bayes NLP model in R, achieving 74.45% accuracy.
• Integrated Lightcast job-posting data with FRED macroeconomic indicators to analyze 2024 U.S. labor market trends, applying NLP and statistical modeling to evaluate hiring patterns, skill demand, and regional wage dynamics.
• Classified stellar variability across 100K+ stars using kNN, Logistic Regression, SVM, and Random Forest models, with Gaussian SVM achieving 71% test accuracy.
• Developed a scalable data integration pipeline processing 3M+ labor market records, integrating multiple data sources into warehouse-ready datasets with automated quality monitoring and anomaly detection. • Developed an AI-enabled labor market analytics platform with interactive Plotly visualizations, enabling students and faculty to explore workforce trends and generate data-driven career insights. • Designed a scalable relational database schema supporting user, advising, and labor market domains, enabling seamless integration of 5 external data sources using PostgreSQL and BigQuery.
Data Science Build Student Consultant
The Build Fellowship
Jul 2025 — Sep 2025
• Performed statistical analysis on a 65,000+ patient diabetes dataset, identifying statistically significant disparities in demographics and treatment outcomes that informed early-stage clinical program design. • Built Power BI dashboards to visualize patient trends and communicate analytical findings to project stakeholders
Full-Stack Software Engineer in Financial Systems
Bank VTB
Feb 2023 — Aug 2024
• Developed Oracle APEX applications for real-time financial risk monitoring, enabling compliance teams to identify suspicious client activity and support regulatory reporting. • Improved query and PL/SQL performance by ~50% using DBMS Profiler, resolving reporting latency across compliance and investment operations. • Built automated data mapping workflows in PostgreSQL and Oracle, ensuring data integrity across engineering and product teams. • Cut feature rollout time by 30% by building high-throughput data pipelines, streamlining delivery and reducing downstream reporting errors.