People Analytics and AI leader specializing in context engineering—architecting and managing the context layers that make enterprise AI accurate, governed, and grounded in organizational truth. More than a decade across advanced analytics, economics, machine learning, statistical modeling, and data visualization, including seven years leading analytics and science teams at Amazon, Expedia, and Merck. Specialize in enriching fragmented HR and workforce data into AI-ready context—structuring knowledge, retrieval, and governance so AI systems link people data directly to business outcomes such as retention, performance, and profitability. Architect end-to-end context pipelines spanning data ingestion, enrichment, vector and knowledge-graph retrieval, and full-stack delivery, with a track record of standing up first-of-their-kind HR science teams and production machine learning platforms. Translate complex technical work into boardroom-ready insight for CHROs and executive leadership, and communicate effectively across technical and non-technical audiences in global, cross-cultural organizations. Technical proficiency in AWS (Bedrock, Q Business, CDK, Glue, S3, Athena, SageMaker, Redshift, QuickSight), vector databases, RAG architectures, Python, R, Spark (via R and Python APIs), React/TypeScript with D3, Tableau, Spotfire, Power BI, Trino, PostgreSQL, and MS Office.
Ikona Analytics, Seattle, WA (July 2025 – Present)
Co-Founder & Chief Technology Officer
- Co-founded a consultancy that helps HR teams design and manage the context layers that ground enterprise AI—capturing organizational knowledge and structuring it into a living, governed intelligence asset so AI becomes a partner in diagnosing and improving organizational gaps, not just automating tasks.
- Architect the context-engineering stack behind the Ikona Intelligence Platform and the AI-powered Ikona Systems Diagnostic (ISD®)—retrieval pipelines, vector stores, and knowledge structures on AWS Bedrock and Q Business that enrich raw HR data into AI-ready context, assessing 1,000+ intersections of the HR ecosystem to deliver executive-ready roadmaps in 30 days.
- Co-direct Fortune 100 client engagements, benchmarking workforce systems against the Ground Truth™ framework and engineering the context that links people data directly to outcomes including retention, performance, and profitability.
- Define company technology and engineering strategy; architect full-stack applications using React 18+, TypeScript 5+, and D3 visualizations on AWS Amplify and serverless architectures that operationalize the context layer as a persistent, queryable asset clients own long after the engagement ends.
New York University School of Professional Studies (NYU SPS), New York, NY (2019 – 2021; 2026 – Present)
Adjunct Instruction Faculty, Certificate in People Analytics
- Teach Introduction to Data Science for HCM in Python and R, equipping HR professionals to apply Python and R to real workforce problems; the course is cross-listed across NYU's Certificate in People Analytics and Certificate in Data Analytics.
- Previously taught HR Workforce Analytics and the certificate's foundational data science curriculum, translating advanced analytics for HR practitioners.
- Build the analytical fluency and data literacy HR teams need to partner effectively with technical and AI initiatives.
Expedia Group, Seattle, WA (November 2023 – July 2025)
Director, Machine Learning Science and Engineering, People Team
- Lead and manage a team of data scientists and engineers to deliver strategic data science initiatives, ensuring alignment with business development roadmaps.
- Oversee the entire data science lifecycle, from data engineering and preprocessing to model development, evaluation, and deployment.
- Drive the development and execution of a comprehensive data science strategy, emphasizing trend forecasting, anomaly detection, and graph analytics.
- Built Expedia's first ever HR science team focusing on CI/CD frameworks to scale and maintain new and existing data pipelines and machine learning models; recruited HR's first-ever machine learning scientists.
- Consolidated anomaly detection and forecasting efforts of talent metrics for the company's Chief HR Officer and her executive leadership teams.
Amazon, Seattle, WA (February 2022 – October 2023)
Lead, Senior Data Scientist
- Supervised end-to-end data science workflows, from data engineering and preprocessing to model development, assessment, and deployment in accordance with business development roadmaps.
- Oversaw a team of data scientists and economists in implementing data science strategy with keen focus on trend forecasting, anomaly identification, and graph analytics for the company's Global Talent Management products and programs.
- Scaled forecasting and anomaly insights to more than 3K managers and talent leads to help facilitate data-driven decision-making processes across all levels of the organization.
- Led the development and rollout of a secure, people-data-friendly machine learning and analytics framework for scientists and software engineers, enabling them to scale models into production systems using the AWS CDK.