New York, New York, United States
Experienced data professional with a strong background in machine learning and data science. Fluent in Python, SQL, Tableau, R, Excel. Highly experienced with cross functional collaboration, excellent communication skills, frequent executive level presentations. Email: [email protected]
• Built and productionized large-scale ETL pipelines processing billions of Alexa utterance-level records and aggregated metrics, while owning data modeling, dataset onboarding and storage, and Airflow orchestration. Supported 30+ organizations in executive decision alignment, customer experience improvement, and company wide data-driven strategies. • Led feature enhancements for production Python packages supporting ~1,000 MAU, strengthened automated testing, and took full ownership of build, test, and deployment lifecycles using Amazon’s internal release systems. Drove the transition of release ownership from Software Engineering team to Data Engineering team, supported live systems through incident response, and coached engineers on package deployment and operational support. • Served as a trusted escalation point during on-call rotations for time-sensitive, high-impact operational decisions, resolving Severity 2 incidents, mitigating operational risks, unblocking delayed pipelines, and addressing urgent ad hoc customer data requests.
• Leveraged Machine Learning modeling techniques for manufacturing root cause identification in Python. • Daily firefighting tasks include presenting to executives, data mining, data processing, ETL, correlation study and data visualization in Python, SQL and Tableau.
• Delivered data analytics, modeling, ETL and Big Data solutions utilizing Python, SQL, Tableau and Big Data platforms to serve clients from diverse sectors, including banking, IT, government, and pharmaceuticals.
• Leveraged Python under AWS environment to build machine learning models to predict future hotel occupancy and to recommend room pricing to maximize overall revenue for hotel revenue managers. • Used SQL and NoSQL to validate billions of records. • Worked directly with CTO on a daily basis.
• Helped UVA Diversity Organization to determine project goals and find resources for data analysis.