Designed predictive models in Python using scikit-learn to identify over 3,000 high-risk patient records, improving care management outreach accuracy and supporting population-health initiatives. Implemented ETL pipelines with Apache Spark and AWS Lambda to process 500,000+ health care claims and reduce data availability time for clinical reporting by 2 days. Partnered with data science and actuarial teams to develop 5 Power BI dashboards integrating cost and utilization data, enabling timely cost-of-care reviews. Built NLP workflows using spaCy and Python to extract insights from 20,000+ clinical notes and strengthen member-engagement analytics; developed anomaly-detection pipelines in Databricks with MLflow to monitor 150+ model anomalies quarterly and maintain data quality.

Data Analyst at General Motors

June 1, 2025 - June 1, 2025

Created predictive maintenance algorithms in Python using scikit-learn to forecast equipment failures, reducing unplanned downtime by 120 hours annually. Built ETL pipelines in Apache Kafka and AWS Lambda to process over 1 million sensor readings daily; collaborated with product managers, engineers, and data architects to develop Power BI dashboards integrating production and reliability data, enabling data-driven operational decisions. Conducted spatial analysis with Esri ArcGIS to optimize dealership locations, driving a 15% increase in market coverage. Led a team of 5 analysts under Agile workflows, improving delivery speed by 30% through iterative development and feedback. Designed centralized Snowflake data warehouse with dbt, promoting cross-team collaboration and reducing data retrieval times by 40% for manufacturing and engineering analytics.

Data Analyst at KPMG

July 1, 2022 - July 1, 2022

Performs data quality assessments on customer and transaction datasets using Power Query and Excel, identifying and remediating over 50 data integrity issues to improve data reliability for marketing strategies. Developed interactive dashboards in Tableau to visualize customer segmentation and transaction trends, enabling marketing to identify top-performing segments and optimize campaigns. Calculated customer lifetime value using Excel and advanced analytics to inform resource allocation for marketing initiatives. Collaborated with cross-functional teams to unify customer and transaction data into a single dataset, streamlining access and reporting across departments. Delivered data-driven insights through comprehensive reports and mentored junior analysts to lift team productivity.