Guide and grow the team of Applied Research Scientists focused on developing state-of-the-art Machine Learning models to serve Nike Commerce Experiences including Personalization, Search, Browse, Recommendations, Wholesale Portals, and SNKRS. Collaborate across Applied Science verticals and cross-functional Engineering, Platform, and Product teams to productionalize Machine Learning use cases in Commercial Analytics, Supply Chain, Product Creation & Merchandising, and Marketing Communications to develop initiatives to export model decision introspection, embeddings, and explainable AI throughout the organization.Drive integrated model development throughout systems to power and optimize Global resources applied to dynamic business requirements.Oversight of ongoing research & development of customer facing digital machine learning systems, the AIR (Artificial Intelligence Recommendations) Personalization Recommender System, Nike's Search System Models (LLM's with Neural Rankers), Browse Curation Systems, as well as a portfolio of in-house Machine Learning models powering various Nike experiences and geographies to personalize every digital touch point of the customer journey.Lead in the development of innovative methods such as Deep Reinforcement Learning for Sort Optimization, privacy and GDPR compliant Neural Candidate Generators, and state-of-the-art Transformer/LLM based Personalization Engines.Contribute to divisional (Consumer Data Science), cross-functional (Global Technology, Geo Enterprise Data), and stakeholder (Nike Direct Product, Nike Digital Core Commerce) strategic planning roadmaps.

Neural Networks: Supervised Learning, MLPs, Deep Learning, RNNs, CNNs, TransformersUnsupervised Machine Learning: Clustering, SVD, Matrix Factorization, Dimensionality Reduction & EmbeddingsExperiential Learning: Search & Recommender Systems

Python & Exploratory Data AnalysisData MiningMachine LearningDeep LearningArtificial Intelligence / Reinforcement LearningSearch & Recommender Systems

Designed architectures & cross-functional roadmaps (Engineering/Platform/Product) for consumer facing system-of-models powering Personalization, Browse, and Recommendations.Developed frameworks for research, experimentation, and rapid implementation of Artificial Intelligence / Machine Learning systems for Product Curation & Recommendations across Global Browse pages and carousels.Developed Neural based Ranking Model over complete catalog of over 20M products for downstream use by Recommendations, Search, and Marketing (A/B Test Winner).Developed Deep Reinforcement Learning algorithm for multi-objective sort optimization over various business KPIs across categorical Browse Walls.Developed robust @k measurement and metrics framework for offline evaluation of recommender systems. Deep Reinforcement Learning Decision Scientist across all dimensions of E-Commerce Platforms for Artificial Intelligence in Default & Personalization for E-commerce Experiences, Behavior, & Process Optimization.Cross collaborative planning & design of metrics, evaluation & analytics for future roadmap development.

Principal Investigator for DeepMission™: Learning in Simulation Applied Reinforcement Learning Platform for multi-domain, multi-agent, operational tactical studies, prototypes & integration, resulting in 20+ User Group, $25M+ program revenue, intellectual property patents, & publications.Principal Investigator for DARPA CHASE System of ML/AI Algorithms, Technical Lead on 10+ DARPA, AFRL programs in Automation, Control & Estimation ($50M+ Scope, oversight of 5-25 person cross-domain teams).Technical Lead & Researcher ($1-$10M) for Competency Aware Machine Learning using unsupervised learning for neural inspection, Multi-Agent Deep Reinforcement Learning with Bayesian Modeling of Human Machine Interaction, Hierarchical Reinforcement Learning for user based constrained targeting.Enhanced Deep Learning Classification tasks using Reinforcement Learning via custom OpenAI Gym Environments, custom WaveNet architecture (RiftNet™), RiftNetXt™ (patent pending), & Mindful™ for Neural Policy Introspection (UMAP, Clustering, SHAP Variants) and Explainable AI.Empower IRAD campaign selections (3), including top award out of over 100 entries for Multi Agent Coordination & Competition Reinforcement Learning studies with Explainability and Introspection.AI/ML White Paper/Proposals ($20M+) co-authorships, lead for Decision Sciences, Game Theory pods2020 & 2019 Nominations for BAE Systems Chairman's Award (Recipient of several Impact Awards).

Technical Lead over several DARPA programs, managing multiple project teams of 5+ in AI/MLCODE Center (IIS) Senior Leadership Team Strategy/Budgeting for 2018 Fiscal YearR&D applications of GAN’s, Bayesian, & Deep Learning models for intrusion detection systemsR&D of information theoretic algorithm for natural language processing (internal IP filed)DARPA Grand Challenge, Finalist (Deep Red - 2016) Python/C++/MongoDB analytic R&DDARPA PlanX Python/C Developer for analytics and game play strategy

Technical Lead over software developers, mathematicians, and legal counsel resulting in $30B+ in auction proceeds, 2018 INFORMS Franz Edelman Prize, future academic/industry formulation reuseApplied Mathematician responsible for interpretation and implementation of auction theoretic mechanisms (from 2020 Nobel Prize Recipient) improving efficiency & solvability of mixed integer optimization formulationsNovel formulation for SVD and PageRank application to network station valuation graphBayesian/ML analysis of empirical data to create subproblem optimizations for mix integer programming optimization resulting in zero value stations for higher optimality solutionsHierarchical Bayesian algorithm optimizing for auction theoretic scoring functions and soft constraintsDevelopment of distributed system architecture & master/sub problem decomposition code to create constraints, graph cuts and branching strategies resulting in 80% run time decrease

Led cross-domain teams consisting of SEO/SEM Analysts, Data Scientists (Digital Commerce), and Data Engineering in support of strategic development and marketing departments for large e-commerce/omni channel client base including AmEx, Jim Beam, BareFoot, NetJets, Philips, Ingersol-Rand.Developed proposals/white papers for new business development and customer growth design along side various teams within Geometry Global and Ogilvy & Mather Managed digital strategy teams for web, social and customer app analytics.Led predictive and time series modeling for advanced client analytics for product growth and insightsSurvey design, cohesive campaign design and execution coordination between customer, internal creative teams including data collection, management and storage planning.

Research Project: ”Developing Efficient Methods For Parallel Data Redistribution On Hybrid Architectures”, Advisor: Dr. Andrew SiegelAdvancing performance/analysis of the C/MPI based application library, The Memory-Aware Data Redistribution Engine (MADRE) (http://vsl.cis.udel.edu/madre/)Integration of OpenMP into MADRE Library for shared memory analysis, Pinar-Hendrickson/Cyclic Scheduler Algorithms analysis for varied input maps, varied memory constraints

Program Manager over internal initiative to develop single data warehouse environment for internal and external analytics, management of cross-departmental team 20+ (5 direct reports).Lead client facing information director/business analyst responsible for client data warehousing, C-Level analysis, presentation of finance and event marketing spend for Cisco Systems, Coca-Cola, Shell Oil, Microsoft, Thomson Reuters, AT&T and MillerCoors representing $10M+ in revenue.Strategic planning oversight over product design, pricing models and marketing channel identification for using warehoused data to be packaged and sold externally to the industry.Manage team of analysts over IBM Cognos and Business Objects powered business intelligence for analytics on data over Maritz/American Express.Implemented dynamic multivariate predictive model based on revenue, spend, cost savings, processes, internal and external market factors used for operations optimization, internal leadership reporting and external vendor reporting.Served on Client Advisory Board for StarCite, Cvent SaaS companies to shape technology roadmaps.

Executive business management consulting to area venture capital firm and area technology firm in their joint partnership to provide disruptive technology and e-Commerce solutions to their customersBusiness and marketing plan creation, organizational structure, pro forma and market research guidance and executionActing Managing Director over suite of product offerings, and serving as acting CEO for products in pre-market stage for positioning with first customer, funding meetings and lean startup implementationFounder/CEO of Method, an Entrepreneurship Incubator program providing real world learning, research and mentorship environment to MBA students at Northwestern University, University of Chicago, DePaul University and Loyola University

Business & Strategic Marketing Plan design, implementation and $1M venture capital funding for Technology/Software Startup in blended e-Commerce / SaaS spaceDesign and measurement of global user group, market research through focus groups, surveys, online feedback, A/B and multivariate testing resulting in a Year-over-Year quantified increase in all user experience metricsCompetitive intelligence analysis to leverage marketplace opportunities and product development for site activityIncreased user group size and retention rates quarter over quarter through SEO, SEM and email campaign strategiesEngineered ERD for multipurpose use as CRM, BI and user data warehouse to capture market research and spend management analysis outputting a Future Market Index (patents pending), predictive modelManaged joint enterprising project between MeetingTrader and MGM Resorts International for proprietary marketing softwareManaged all functional development areas, Operations Managers, Developers, Sales and third party Marketing Agencies