Pamela Krueger is a Principal Data Analytics Analyst with over six years of experience in analytics, data science, research, program development, management, and evaluation. Currently serving as the Global Post-Market Artificial Intelligence (AI)/Analytics Strategy Leader at Boston Scientific (BSC), she is a prominent figure in the analytics field.

Krueger holds bachelor's and master's degrees in economics from prestigious universities, with a specialization in research methods, mathematics, statistics, and health economics. Her technical expertise includes proficiency in Python, SAS, Stata, C#, SQL, Tableau, and SAS Visual Analytics. She is dedicated to advancing her knowledge in machine learning and cloud-based platforms like Amazon Web Services (AWS).

Throughout her career, Krueger has played diverse roles, including Research Scientist 3 at the Minnesota Department of Human Services, Health Systems Specialist at the Hawaii State Dept of Health, and Researcher and Health Economist at the University of Hawaii at Manoa. She has also contributed her skills to international organizations such as Chemonics International, UBELONG, and The International Foundation for Electoral Systems, where she held various positions.

As an active member of the professional community, Krueger co-leads BSC's Advanced Analytics Community of Practice and was a Planning Leader for the 2020 BSC Global Analytics Summit. She serves as a technical advisor to senior leadership at BSC, providing insights on advanced analytics technologies and methods.

Krueger's educational journey includes studies in Mathematics, Statistics, and Computer Programming at the University of Minnesota-Duluth, Research Methods for Development at The Johns Hopkins University, Economics and Public Policy at Georgetown University, and Economics at the University of Wisconsin-Madison. She completed her B.A. in Economics, Spanish, and Chinese at the University of Minnesota-Twin Cities.

In summary, Pamela Krueger is a seasoned professional in data analytics, with a strong background in various analytical tools and methodologies, extensive industry experience, and a commitment to continuous learning and growth in the field of analytics and data science.