Delivery-focused business science and organizational leader with in-depth understanding of advanced analytics, economic analysis, machine learning, statistical modeling, and data visualization. Seven years of experience managing analytics and science teams; proven capacity for applying principles of data governance, data management, data security, and process simplification in contributing to the development of analytical tools for people programs. Demonstrate strong problem-solving and critical-thinking competencies, exceptional eye for detail, excellent cross-cultural communication and presentation skills, and outstanding ability to effectively convey complex ideas to both technical and non-technical audiences, including other data scientists and analytical engineers in global organizations. Technical proficiency in AWS (CDK, Glue, S3, Athena, SageMaker, Redshift, QuickSight), Python, R, Spark (via R and Python APIs), Tableau, Spotfire, Power BI, Trino, PostgreSQL, and MS Office.
Expedia Group, Seattle, WA (November 2023 – Present)
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.