Innovation Manager for Data Science with the Office of Innovation's Frontier Tech Team. Provide technical advisory on data science, machine learning and AI to UNICEF programmatic operations. This includes supporting learning, healthcare, innovative finance, climate and sanitation projects benefitting children around the world.

AI and Data Science Mentor for social enterprise startups backed by the UNICEF Office of Innovation's Venture Fund. Provide technical guidance and review support on data science/machine learning/AI applications to social good startups from the developing world. Promote open source initiatives and digital public goods.

White House Presidential Innovation Fellow detailed to the US Geological Survey (USGS) Energy and Minerals Resources Mission Area supporting mission-critical data strategy objectives. These support administration priorities around supply chain resilience, climate adaptation and national security.The Presidential Innovation Fellows program pairs technologists and innovators with top federal change-makers to catalyze a modern government for all.Supported effort to revise the Federal Open Data Policy and Guidance issued by the US Office of Management and Budget (OMB).

- Presented recommendations to senior leadership of the USGS Energy and Minerals Mission Area to enhance data management and data product delivery. - Developed a project strategy for data management and product delivery for the Earth Mapping Resources Initiative, the largest geospatial reconnaissance for geoscience properties of the US lands and subsurface in the history of the US. - Provided technical support for a DARPA/USGS/ARPA-Energy co-sponsored competition for the development of multimodal AI models to enhance critical minerals assessments to locate and estimate the potential for critical minerals sites in the territorial US

Develop machine learning models and data science tools for Internal Audit, Risk and Intelligence activities. Highlights include: - Development and deployment of anomaly detection on employee expense claims using machine learning and business knowledge. Incorporated business processes and company policies to inform decision-making for internal stakeholders. - Development and deployment of time series models to identify anomalies payroll tax expenses. Used model estimates to support SOX controls process by the Tax Accounting units.- Filed patent in United States Patent Office on Hybrid Approaches to Anomaly Detection in Journal Entries.- Filed patent in United States Patent Office on Automated Anomaly Detection using Machine Learning and Binary Point Anomaly Methods (in progress)- Project management of data science projects overseeing process workflows from data engineers, DevOps, machine learning engineers and intended stakeholders.

I served as the World Food Programme's pioneer data scientist for global cash transfer operations from HeadQuarters. My primary responsibilities included assisting country offices worldwide with technical support in building data analytical capacity and risk management practices to provide accountability and transparency to stakeholders (programme officers, senior management, donors) in humanitarian aid programs. Key data science work streams include deduplication of registries, anomaly detection and risk analytics in cash transfers aid delivery. I designed the deduplication device behind the coordination of assistance between NGO actors and UN agencies for the Venezuela migrant crisis response in Colombia as well as the Beirut explosion response in Lebanon (2020). I developed and evangelized the global cash-based transfers Anomaly Detection Framework as guidance for anomaly detection in cash transfer operations globally. I apply machine learning, predictive analytics and business intelligence approaches to identify process operations issues and also guide management to address these issues. I represented the World Food Programme in coordinating committees on strategic partnerships with other UN agencies in the cash transfers space.I provided support to program responses in countries in the Syria refugee crisis region, Venezuela migrant crisis region and sub-Saharan Africa. The UN World Food Programme was awarded the Nobel Prize for Peace in 2020. I am proud to have contributed to its mission. Tools:: Python, SQL, PostgreSQL, AWS, S3, R, Tableau, Azure DevOps, SAP HANA

I have worked on strategic initiatives for critical regulatory compliance activities related to stress-testing at the Enterprise level. I have devised scenarios for stress-testing, organized data validation efforts and performed risk analysis on stress-testing outcomes. Main highlights included:• Produced and evaluated credit and equity loss estimates for USAA’s investment portfolios • Evaluated forecasting models for estimating forward-looking losses for the company (SAS)• Led Reverse Stress Testing efforts and quantified scenario impacts in Python/R

Performed risk analysis of financial positions in the Federal Reserve Bank's portfolios. * Used data analytical tools (SAS, SQL server, Intex, Bloomberg, other proprietary software) to perform price verification and valuation of Federal Reserve Bank portfolio holdings and Discount Window collateral.* Collaborate with business groups from around the Federal Reserve System in support financial operations.* Perform risk evaluation of supervised financial institutions' financial stress-testing results.

Performed analysis on the counterparty, market and credit risk profiles of regulated financial institutions.• Analyzed and stressed Credit Valuation Adjustment (CVA) inputs and trading and credit incremental default risk data provided by large financial institutions as part of a comprehensive review of institution’s capital action plans• Analyzed counterparty credit risk data from large financial institutions to evaluate firm CVA estimation and methodology • Used Stata to estimate probability of default for the largest counterparty exposures for large financial institutions• Performed time series analysis on daily and weekly data provided by large financial institutions on large counterparty credit and funding exposures• Participated on market risk exams focused on equity derivatives products at a large financial institution• Co-wrote business proposal for the acquisition of OTC derivatives pricing tool (Totem)• Researched and wrote about the mortgage banking business of a large financial institution as part of the central point-of-contact (CPC) team• Wrote 5 institutional overviews/strength of support assessments of foreign banking organizations• Developed head office organizational structure chart of a complex foreign banking organization• Performed loan review and CAMELS analyses for regional banking organizations

Provided research support for leading industry experts assisting large companies in publicized legal cases. Key workstreams included:- development of cash flow model for generation of financial damages claims- manipulated and analyzed complex data sets in SAS, Stata and MS Office applications