• Aided the Amazon Fraud Detector “AFD” team of Amazon Web Services in developing new business logic for Amazon customers to view performance of machine learning (“ML”) based fraud models using Java

• Implemented customer facing component (React / NodeJS) of batch ingestion feature, allowing customers to quickly import historical event data--both fraudulent and legitimate--for quicker model training leading to faster model implementation

• Expanded a backend system to asynchronously vend large batches of ML fraud prediction results to customers using python.

• Managed multiple continuous integration pipelines for releasing new features to production accounts and fixed blocked pipelines by modifying broken integration tests to ensure clear pathways from development to production

• Coordinated with project managers, application security, and technical writers to design and release four features in two months

• Responsibilities include: developing due diligence plans, reviews of managers’ documented procedures, attending onsite and offsite meetings, preparing written analyses of managers’ business and operational capabilities

• Develops knowledge and keeps abreast of dynamic changes with respect to industry standards and best practices impacting operational due diligence especially in technical fields

• Review and monitor audited financial statements and ongoing operational developments at investment manager firms

• Non-profit organization that guides young entrepreneurs and future innovators by empowering them with the essential experience, mentorship, and resources to grow their startups exponentially.

• Communicate objectives between the board, management, and members.

• Ensure notice compliance to donors in accordance with bylaws.