Iain Brown
Head of Data Science, SAS
Dr. Iain Brown is Head of Data Science at SAS, specializing in Credit Risk. Prior to joining SAS in 2011, he worked as a Credit Risk Analyst at a major UK retail bank where he built and validated PD, LGD, and EAD models using SAS software. He has spoken at a number of internationally renowned conferences and conventions and has published papers on the topic of credit risk modeling in the International Journal of Forecasting and the Journal of Expert Systems with Applications. In 2011, he won the SAS Student Ambassador award for his doctoral research, which recognizes and supports students who use SAS technologies in innovative ways to benefit their respective industries and fields of study.
Iain has a BBA in Business from the University of Kent, an MSc in Operational Research from the London School of Economics and Political Science (LSE), and a PhD in Credit Risk from the University of Southampton. Iain is also an active member of the Operational Research (OR) Society; in July 2014, he was awarded the title of Associate Fellow of the OR Society (AFORS) for his contribution to the field of OR. His research interests include data mining, credit scoring, credit risk modeling, and Basel compliancy.
By This Author
Financial Data Science with SAS®Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers
By Iain Brown
Unlock the Power of Data: Transform Your Marketing Strategies with Data Science
In the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers, Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively.
- Comprehensive Coverage: From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science.
- Practical Applications: Engage with real-world examples, hands-on exercises in both Python & SAS, and actionable insights to apply in your marketing campaigns.
- Expert Guidance: Benefit from Dr. Iain Brown's decade of experience as he shares cutting-edge techniques and ethical considerations in marketing data science.
- Future-Ready Skills: Learn about the latest advancements, including generative AI, to stay ahead in the rapidly evolving marketing landscape.
- Accessible Learning: Tailored for both beginners and seasoned professionals, this book ensures a smooth learning curve with a clear, engaging narrative.
Mastering Marketing Data Science is designed as a comprehensive how-to guide, weaving together theory and practice to offer a dynamic, workbook-style learning experience. Dr. Brown's voice and expertise guide you through the complexities of marketing data science, making sophisticated concepts accessible and actionable.
Developing Credit Risk Models Using SAS® Enterprise Miner™ and SAS/STAT®: Theory and Applications
By Iain L. J. Brown
*This book is out of print.
Featured Authors
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.