- Orchestrated the SDLC for an enterprise ML initiative, aligning data science, engineering, and business stakeholders around a roadmap to automate element-level data lineage mapping.
- Accelerated data coverage to 99% by coordinating cross-functional agile delivery of an ML inference utility, eliminating manual column mapping across pipelines serving billions of lineage events.
- Validated product direction via discovery interviews across 5 enterprise teams; prototyped workflows in Figma.
- Presented findings to senior leadership to drive consensus on ML roadmap priorities across sprint cycles.
- Engineered a reproducible R-based geospatial ETL pipeline integrating multi-source GLS seabird tracking data with oceanographic covariates (SST, chlorophyll-a, wind fields).
- Implemented movement ecology analytics including kernel utilization distributions (50%, 95%), centroid analysis, and displacement metrics to model migration patterns.
- Developed GAMMs to identify habitat-use drivers and fisheries-overlap risk; produced geospatial visualizations for wildlife management stakeholders.
- Drove product strategy of a WhatsApp-based AI advisory assistant for farmers; conducted 100+ user interviews and scaled to 350+ farmers receiving real-time crop and field guidance.
- Designed the system architecture and MySQL schema to analyze 10K+ messages, surfacing behavioral patterns through a KPI dashboard.
- Architected a multi-agent LLM pipeline classifying farmer queries across 4 intent categories and 30 agricultural query types.
- Defined security mitigation product roadmaps for enterprise clients by synthesizing threat intelligence across three reports.
- Stress-tested client security strategies against 10 real-world APT attack patterns, validating 85% MITRE ATT&CK coverage.
- Turned 20K+ raw threat feeds into a structured risk prioritization framework, enabling proactive threat-informed planning.