Daniel (Dan) Lieb
About Daniel (Dan) Lieb
Daniel (Dan) Lieb is the Senior Director of Data Science and Head of Artificial Intelligence and Machine Learning Model Risk at Ally, with extensive experience in data science and risk management across various financial institutions.
Current Role at Ally
Daniel Lieb serves as the Senior Director of Data Science, Head of Artificial Intelligence and Machine Learning Model Risk at Ally, a position he has held since 2023. In this role, Daniel focuses on overseeing AI and ML model risk management. He leverages his extensive expertise in advanced analytics, modeling, and various data science tools to mitigate risks associated with AI implementations.
Previous Experience at Ally
Before his current role, Daniel worked at Ally as the Senior Director of Data Science, Head of Artificial Intelligence Data Products from 2019 to 2023. During this period, he led initiatives on AI data product development, applying real-time decision-making and personalization to enhance customer experiences. His work involved extensive use of machine learning platforms and advanced analytics tools.
Career at Wells Fargo
From 2012 to 2019, Daniel Lieb held multiple positions at Wells Fargo. As the Senior Data Science Risk Manager for Commercial Credit Risk, he worked from 2016 to 2019 in Charlotte, North Carolina. Prior to that, he served as a Lead Data Scientist in Home Lending Marketing from 2013 to 2016. He also held the role of Data Science Strategy Manager for Email Marketing from 2012 to 2013. In these roles, Daniel applied his skills in data science to manage risks, develop marketing strategies, and enhance lending processes.
Education and Academic Background
Daniel Lieb earned his Ph.D. in Marketing Econometrics from Duke University's Fuqua School of Business, where he studied from 2001 to 2007. He also holds an M.S. in Management Science and Operations Research from Stanford University, completed in 1998, and a B.A. in Mathematics from Wesleyan University, completed in 1997. His academic background laid a strong foundation for his career in data science and analytics.
Technical Proficiencies and Data Science Tools
Daniel Lieb is experienced with a wide range of data science tools and platforms. He utilizes AWS, Microsoft Azure, and Cloudera for infrastructure needs, and employs languages and tools like Python, R, SAS, SQL, and Alteryx for advanced analytics and modeling. His expertise extends to machine learning platforms such as SageMaker, DataRobot, and H2O AI. For data visualization, he uses tools like Power BI and Tableau, and manages large datasets using databases such as Snowflake, Teradata, Oracle, and DB2. Additionally, he integrates enterprise applications like Adobe Analytics, Pegasystems Customer Decision Hub, and Celebrus.
Professional Experience in the Financial Sector
Prior to his roles at Ally and Wells Fargo, Daniel Lieb worked at Bank of America from 2009 to 2012 as a Data Science Manager in Home Lending and Insurance, and from 2007 to 2009 as a Data Scientist in Credit Card Marketing. He also gained experience at Intel Corporation as an Advanced Business Analyst from 1999 to 2001 and at Oracle as a Business Analyst from 1998 to 1999. These diverse roles enriched his expertise in managing and analyzing data across various financial domains.