Data Scientist
CurrentInformation TechnologyData Science & Analytics ChapterEnterprise Data & Insights Innovation Team• Leading in-house development of oil field leak detection MVP, including facilitating team touchpoints, training computer vision models, developing an end-to-end pipeline (from image retrieval to results visualization in a web app), integrating with existing Chevron systems/tools, coordinating field trials, and refactoring codebase for production implementation• Contributing (or have contributed) to several other computer vision use cases, including: building footprint detection for high consequence area identification along pipeline right-of-way; real-time pipeline surveillance to detect potential threats; and "man down" detection to enable urgent response to emergencies such as falls or other health crises• Participate in Computer Vision Capability Council to grow capabilities, share knowledge, and gain alignment with a diverse group of computer vision practitioners within Chevron• Support the team's alignment with enterprise-wide computer vision innovation goals, especially through facilitation of the Computer Vision Working Group, as well as maintaining a computer vision use case tracking tool and contributing to a corresponding "point of view" document• Collaborate closely with Geospatial Technology & Analytics and Azure Accelerators & Consulting teams in order to experiment with, provide feedback on, and develop an internal SpatioTemporal Asset Catalog (STAC) GUI and other geospatial tools/workflows• Participated in the Maven Automated Insights Design Sprint (as well as preceding scoping discussions, workshops, and stakeholder engagements), during which the team built an interactive prototype of a self-service computer vision system to generate insights on visual data, then subsequently tested it with real users to gather feedback and identify areas of improvement for future iterations• Serve as a buddy/mentor for data science interns each summer
