I formed and lead a team that works on strategic initiatives with company-wide impact and executive visibility. This includes areas such as generative AI, ML governance, infrastructure optimization, and future business expansion opportunities.

I head the TPM group that supports Uber's AI and ML functions, with initiatives ranging from our ML platform (Michelangelo) to applied AI/ML in our products (e.g., recommendations, personalization).I lead Uber's Data Science and Machine Learning Council, a cross-organizational architecture group that sets direction and strategy for AI/ML at the company. This includes tasks such as reviewing/overseeing the quality of ML models, measuring productivity, and supporting growth/excellence for Machine Learning Engineers and Applied Scientists. I also co-lead Uber's Generative AI Steering Committee, which sets the company's strategy for GenAI investments, and I am a core member of the team that drives Uber's Responsible AI and governance initiatives.

This was a senior IC TPM role in Uber's AI/ML organization (UberAI), where I focused on cross-Uber Personalization and Search/Discovery initiatives.

I led strategy and product for the Data Science, Data Platform, and AI Services pillars of SAP's Intelligent Spend Group, where we were using cutting-edge technologies (e.g., big data, graph, AI/ML) to link the world's financial information. These connections created exciting new insights for our customers in areas ranging from procurement to expense management. My primary responsibilities were:• Setting vision, strategy, and direction for platform services and products, including determining which services should be built and which ML/AI insights should be pursued.• Owning a product portfolio for platform services, including (1) an extensible MatchingService that leveraged machine learning and rules to uncover and build relationships between data, (2) a graph database that supported time-series data, and (3) data quality, acquisition, and reconciliation services that fetched, fixed, and backfilled data.* Being accountable for the roadmaps of multiple engineering delivery teams; managed several executive-level collaborations and joint products.• Managing a team of Product Managers, each of whom was embedded in an engineering team.• Overseeing the Data Science team, providing guidance and leading collaborations with other research teams across SAP.Key highlights:• Represented organization at SAP TechEd 2019, giving two talks and running two workshops.• Initiated and launched SAP’s highly-visible Disruption Exposure report, a free offering to our customers to help them navigate supply chain disruptions during COVID-19.• Created and released a new ML-based data matching and quality scoring system, which manages large-scale heterogeneous data.• Spearheaded multiple innovative co-development projects within SAP and with its partners/customers.

• Head of Developer Experience in EADP (EA Digital Platform), a central CTO-led organization that builds the core technologies that power EA’s AAA-level video games.• Created strategy and owned roadmaps for the Player & Developer Experience (PDE) organization (>100 FTEs), which included presenting to the CTO, CIO and other executives.• Envisioned and launched the EA Console, an extensible Web portal framework for managing EA’s game development technologies (similar in concept to the AWS Console).• Accountable for EADP’s efforts towards standardization and platform interoperability.• Directly managed a diverse team (8 FTEs) that included PMs, UX designers, developers andtechnical writers; Set and oversaw work of engineering teams and technical directors.

• Defined and drove the technical vision of a big data consulting and product development startup, which used Hadoop (Hortonworks, Cloudera), Spark, Hive, AWS, Cassandra, Kafka, and other technologies to develop highly scalable data processing and analysis solutions.• Assisted clients in digital transformation initiatives and cloud migration projects.• Successfully initiated and managed new contracts and engagements, including leading pre-sales meetings, writing Statements of Work (SOWs) and negotiating deliverables/pricing.• Worked hands-on with customers (incl. C-levels) to identify problems and design solutions,including reviewing and delivering architectures and troubleshooting complex systems.• Grew company from three co-founders to a team of >15 FTEs and >$1M of revenue in thefirst six months of operation.• Recruited new talent, supervised and mentored employees, and facilitated training sessionsto increase team’s effectiveness while growing individuals in their roles.

Technical Program Manager working on large-scale data integrity challenges in Amazon's retail catalog. My team created Machine Learning (ML) models and rules (using Hadoop/Spark) that built relationships between items in Amazon's international product catalog. Primary contributions included:• Lead efforts and drive completion of 4 S-Team (SVP-level) company-wide goals, involving all 11 of Amazon’s worldwide marketplaces.• Developed and drove strategy for Catalog Quality’s Darwin group, which used Machine Learning models, >500 EC2 nodes, Hadoop and EML to detect duplicate products.• Successful in designing, proposing to my VP, and launching Amazon’s first seller-facing crowdsourcing experience, which allows sellers to fix problems in Amazon’s catalog.• Managed and led cross-organizational development teams on high-impact strategic development projects, which were deployed to all 11 of Amazon’s worldwide marketplaces.• Promoted new forward-thinking strategies to achieve goals, including the management of cross organizational projects from design to launch.• Enabled and advanced teams by creating roadmaps, strategies and plans while promoting technical excellence, team success and growth through Agile methods.• Built, and managed cross-functional teams on highly visible technical projects that impacted both internal and external business.• Collaborated with and acted as a primary point-of-contact for a diverse set of stakeholders.

Software architect and developer at a consulting company, where I primarily worked on a new and strategic big data initiative for Disney ABC Television. The project's goals were to leverage cloud-based big data platforms to gain actionable insight from viewership data. My contributions involved both design/architecture tasks and also hands-on creation of cloud-based Hadoop ecosystems and data processing/analytics pipelines.Primary contributions included:• Led and grew eSage’s technical and operations team that spearheaded the creation of a new AWS hosted big-data platform for Disney’s ABC Television Group (DATG).• Migrated complex data workflows and analytics solutions from on-prem. to Cloud solutions.• Architected and deployed large-scale data hosting and processing infrastructures, both on bare-metal and Cloud environments. (AWS, EC2, S3, EMR, Hadoop, HDP 2.x, Hive, Spark).• Constructed data ETL processes to transform large heterogeneous data sets into reliable and usable data. (Java, Perl, Bash, Cron, Oozie).• Designed and implemented data schemas to expose and link usable data. (Hive, Hue).• Grew company’s core competencies and excellence in big data and DevOps by recruiting, training and mentoring new team members.• Worked with stakeholders from the pre-engagement stage and throughout the project lifecycle to identify and deliver on their needs and vision for “big data.”

Researcher in the Data Science and Analytics lab (DataLab) at the University of Washington’s Information School (iSchool). My research topics focused on analyzing large, heterogeneous data to understand why individuals, consumers, and societies behave the way they do.Primary contributions included:• Researched, designed, evaluated, and deployed several computational environments for data analysis and machine learning (e.g., Hadoop, HDFS, MapReduce, Hive, Spark, R).• Contributed to broader efforts of the DataLab research group, which included using machine learning to extract insights from large-scale datasets.• Data ETL of terabyte-scale telecommunications metadata to extract key information from heterogeneous datasets for different types of analysis (e.g., mobility and network structure).• Collaborated with other campus Data Science initiatives (e.g., UW Data Seminar series, eScience Data Incubator) to develop new solutions for large-scale data processing.• Published and presented original research in the areas of network computing and data analysis/processing; acted as reviewer for other research for international conferences.

Developer at a consulting company that builds software for a variety of customers, from Fortune 500 companies to government agencies. Primary contributions included:• Co-designed and architected a real-estate management system (C#, Silverlight, SharePoint, MVVM, WCF RIA, Waterfall). Wrote requirements, design documents and testing plans.• Rewrote a financial management system (C#, InfoPath, SharePoint). Streamlined the development process by automating deployments with PowerShell scripting.• Maintained a legacy codebase for a Web-based real-estate management system (lines: 37K Visual Basic, 11K ASP, 5K other languages). Fixed numerous bugs, refactored code, and enhanced the system with additional features.

Researcher in the Distributed & Scientific Computing group at Cardiff University's School of Computer Science & Informatics. I got funding for and ran several research projects in large scale distributed networks, data distribution, and collaborative environments.Primary contributions included:• Co-Principle Investigator/manager on several large and well-funded ($2M+) multi- institutional research projects; work included envisioning and co-writing proposals.• Directly managed engineering teams and led collaborative efforts at other research labs.• Officially represented university at project reviews and was on decision-making panels.• Researched and developed an innovative and new distributed data management software system for managing scientific data in large-scale wide area networks (Java, C).• Published and disseminated research results at international conferences and workshops (over 20 peer-reviewed papers); reviewed and oversaw other academic research.

Researcher in the Core Computing Sciences focus area of a multidisciplinary research center (CCT) aimed at developing leading edge software technologies. I was responsible for creating and leading the Collaborative Environments Group and spearheading many high-performance Grid infrastructure initiatives.Primary contributions included:• Founded and led the Collaborative Environments Group, which focused on building Web portals (Java, JavaScript, JSP, Spiral) for scientific application groups. The group built solutions for petroleum engineering, coastal modeling, astrophysics, chemistry, and more.• Managed several graduate students and researchers (maximum of 7 concurrently). Contributed to the interviewing, evaluation, and hiring of new employees.• Integrated several high-performance computing clusters and supercomputers into regional and international Grids. Oversaw security and advised other groups on Grid solutions.

Researcher in the computational sciences group of the Astrophysical Relativity Department. My time was split between working on high-performance computing infrastructures and leading the technical development of an online highly-interactive scientific journal.Primary contributions included:• Lead architect of the Living Reviews online journal. Responsible for technical development and design of journal site and processing backend (Java, Perl). Six editorial staff in total.• Co-developed an online portal (GridSphere) to interface with high- performance computing systems. GridSphere (Java, JavaScript, JSP) was a multi-tier (MVC) Portlet framework.• Developer for the Cactus Computational Toolkit (C, Make, and Perl), a parallel computing framework or large-scale data analysis and simulations.