Machine learning has evolved past an esoteric technique worked on by academics and research institutes into a viable technology being deployed at many companies. Machine learning has been significantly changing the competitive landscape of business models worldwide, contributing to the demise of established business, such as Blockbuster, to creating entirely new businesses, such as algorithmic advertising. This presentation strives to address the questions of what assurance professionals need to know about this technology and how to provide assurance around machine learning implementations and its unique risks.
Principal Machine Learning Auditor
Andrew Clark is a Principal Machine Learning Auditor at Capital One where he is creating machine learning powered applications to reinvent the audit process. He is also establishing approaches for auditing machine learning solutions. He is passionate about bringing the best of the open source and data science communities to auditing to shift the auditing paradigm from a reactive to a proactive posture.
Andrew received a B.S. in Business Administration with a concentration in Accounting, Summa Cum Laude, from the University of Tennessee at Chattanooga, an M.S. in Data Science from Southern Methodist University, and is a Ph.D. student in Economics at the University of Reading. He also holds the Certified Analytics Professional, American Statistical Association Graduate Statistician, and AWS Certified Solutions Architect - Associate certifications.