Research Engineer at CreamCollar (2025-07 – Present)
Research Engineer focused on data engineering and compliance frameworks
- Reduced pipeline build time by 30% and improved data consistency across cross-functional teams, by architecting ontology-based data ingestion frameworks for structured and unstructured compliance datasets.
- Eliminated 40% of requirement traceability gaps across 100+ system components, by engineering an automated SDV compliance data pipeline for automotive cybersecurity (UNECE R155) and functional safety standards.
Research Analyst Intern at CreamCollar (2024-07 – 2025-06)
Research Analyst Intern working on data modeling and pipeline development
- Reduced data dependency resolution time by 25%, by designing and implementing a Neo4j graph data model to map complex system relationships across 50,000+ automotive component records.
- Enabled 3 key product decisions by building end-to-end data collection, cleaning, and transformation pipelines on 50,000+ records using Python and SQL, improving data reliability for downstream analytics.
