- Develop and mature Microsoft Research (MSR) Application Security program from its early stage. Author and publish AI+R Security Assessment Standard Operating Procedure, Security Review process diagram, scope and streamline process for early customer engagement, proposing Proactive Engagement Strategy- As 1 of 6 key stakeholders for MSR compliance, partner across Accessibility, Legal, Naming, Online Readiness, Privacy, Security to collaborate with internal customers in their innovation delivery - including to high-profile, external partners- Launch Daily and Weekly Triage Sync to ensure continual realignment of priorities and customer engagements of 15-20 releases at a time by leveraging Power BI dashboards to gauge approach and deliverables for successful, timely customer launch- Solve complex, inherited security strategies that put customers at risk. Backed with data and visualizations, identify root cause and present a structured plan for immediate course-correction and long-term solution to Director of Compliance - denoted with special recognition to and by GM of organization- Lead first ever Post-Mortem for MSR Non-Compliance Event. Responsible for creating the Post-Mortem Template that is being used for future MSR Events/Incidents retrospective- Contribute to Ethics/False-Positives in AI Risk/Threat Model Hackathon with notable contribution for Indonesian company (Microsoft potential partner) looking to reduce accidents due to fatigue using Cognitive AI technology- Lead research in OSS risk. Writing the OSS Story to be presented to EVP of AI+R. Deep-diving/auditing shipped projects for more accurate picture of risk AI+R carries as the biggest consumer of OSS/dependency that will shape AI+R security strategy

- Independently investigated and solved complex, fraudulent cases • Exceeded productivity goals by 55% within the first 3 months • Maintained decision quality above 99% (exceeded target by ~11%) • Oversaw team escalations and gave second opinions for complex cases- Worked closely with engineering to ensure automatic-fraud detection (ML) algorithms continually improved with better training data - Presented to executive and legal team on investigation process to share “tribal” knowledge, making suggestions for process improvement by exposing and providing data analysis of loopholes- In charge of the training program, trained new-hires and teams- Lead a massive process improvement and overhaul of outdated department and team SOP’s - presented to and approved by executives, the SOP and legal team prior to company launch