Conceptual Variable Design for Scorecards: A Standardized Methodology for the Model-Building Process - Paperback
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What You Will Learn
- Harness the power of conceptualization to create models that solve real-world problems. Design meaningful variables that reflect the behaviors of your target population. Expand variables with temporal patterns to capture trends and dynamic changes. Master data integration to streamline preparation and avoid common pitfalls. Implement a unified workflow to simplify and accelerate the modeling process. Explore a larger number of variables in your multivariable models by harnessing the use of experimental design and hyperoptimization.
Who This Book Is For
Professionals engaged in the practical construction of models who seek to gain a comprehensive understanding of the model-building process.
Saul Rodrigo Alvarez Zapiain brings over two decades of diverse professional experience to his role as a principal analytical consultant at SAS. His journey began with a bachelor's degree in industrial biochemical engineering, followed by a master's degree specializing in mathematical modeling of cellular organisms. Having started his career in industries such as pharma, telco, and market research, Saul transitioned to analytics, and while working at Santander, he discovered data mining, sparking a continuous quest for knowledge in analytical domains.
Around 16 years ago, while working at Santander, Saul discovered data mining, sparking a continuous quest for knowledge in analytical domains. Over the years, he honed his skills through self-education and numerous SAS courses, earning over 10 certifications, including Certified Data Scientist and Certified Professional in AI, Machine Learning, and Data Curation. Delving into specialized statistical techniques, he developed a deep understanding of the modeling process. It wasn't until Saul was invited to present his expertise at a conference organized by the Customer Success division that he fully recognized his niche--building models. This realization, coupled with his wealth of real-life experiences, shaped his approach to analytics and problem-solving.
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