Next Meetup

AI in Financial Services – The Final Mile of a Debit Card Fraud ML Model
*New Address* 51 University St. (Suite 300) Seattle, WA 98101 Note: Enter around the the corner at Kaplan entrance on Alaskan Way There will be a Metis sign and staff outside directing guests into the building. Please sign in at the front door. If you cannot attend live, this event will also be Livestreamed. https://livestream.com/accounts/23925505/events/8340609 Today, credit and debit card fraud detection machine learning models are a critical component of a financial institution’s fraud mitigation operations. Predictive performance of these models is extremely important to help catch fraudsters and shut down a customer’s compromised card as soon as possible. Because of this, data scientists often focus all efforts on the training phase of the model life cycle, trying to squeeze out as much predictive power as possible. In highly regulated U.S. banks, and really anywhere one is deploying machine learning models for critical business results, carefully delivering the models that final mile into production can be just as important. In this talk, we explore two ways data scientists can help deliver in the final mile: Gradient Boosting Machine (GBM) fraud model interpretability and model monitoring. Matthew Schlachtman has worked at Wells Fargo for five years and has eight years of data science experience overall. Matthew’s role at Wells Fargo has had many different terms, including data scientist, data engineer, and machine learning engineer, as well as the less defined UAT engineer or data wrangler. Lately, his background in systems architecture, and experience in Machine Learning and H2O have led him to be a lead project architect in the design of a MaaS Architecture at Wells Fargo. Matthew studied autonomous robotics in grad school and eventually transitioned to using his Computer Science and Artificial Intelligence background for non-physical applications. About Metis Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs based in Seattle, New York, Chicago, and San Francisco. Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, and more. Students and alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science. Learn more about us at https://thisismetis.com (https://thisismetis.com/) Join our Metis Community Slack channel! Apply here: https://bit.ly/metis-community-slack Metis Code of Conduct Metis is dedicated to providing a harassment-free experience for everyone, regardless of gender identity, age, sexual orientation, disability, physical appearance, body size, race, or religion (or lack thereof). We do not tolerate harassment of students, staff, or visitors in any form. Sexual language and imagery is not appropriate for any event including talks, workshops, parties, and other online media. Individuals and groups that do not abide by these rules will be asked to leave and, if necessary, prohibited from future events.

Metis Seattle (Kaplan International English - Seattle)

51 University St. Suite 300 · Seattle, WA

What we're about

Metis (http://www.thisismetis.com/) accelerates the careers of data scientists by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, and corporate programs.

We host data science events for aspiring and practicing data scientists and are happy to partner with existing Meetups who would like to collaborate on events in our space.

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