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Tuesday, March 19, 2019 
11:30 AM - 12:30 PM
Machine Learning is being implemented across our enterprise to further leverage the potential of existing data assets to help solve problems in innovative ways. Teams across the enterprise have come together to learn about Artificial Intelligence and Machine Learning, experiment, and collaborate to implement many pilot projects/POCs. But how did Machine Learning get from being just an idea to a concerted effort that led to a subsequent culture shift across departments? Learn how FINRA hit the ground running with ML by facilitating cross-department communication, getting staff the proper support and training, and identifying and prioritizing opportunities for implementation.
Attendees will learn:
- How to identify use cases for Machine Learning and determine their viability
- How to leverage existing datasets for labeling and use in ML-Models
- Techniques to empower and support staff to build necessary skillsets to work in an ML environment
- Approaches to gain support from and partner with the business
Kristen Serafin has worked at the intersection of technology and finance for eight years, ensuring data quality and managing data in a variety of roles. In her current role as an Associate Director in FINRA’s Market Regulation Technology department, she oversees a group that utilizes a wide variety of technologies to sift through big data in order to detect and escalate instances of potentially manipulative activity in the financial markets.
Lizzie Westin has over 20 years of experience in a variety of data-related roles, including analysis, data integration, content operations, data quality management, program management, and product management. In her current role as Associate Director on FINRA’s Enterprise Data Management team, she oversees third-party data management and facilitates cross-business conversations to create a strategic view of third-party data, coordinate new content opportunities at the enterprise level, and expand knowledge sharing about data and related topics.
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