June 9, 2021,
4:30 PM
UTC
09:30 - 09:40 PDT
Introduction
Take part in a series of interactive sessions that focus on tackling pressing industry challenges & opportunities with Senior Data & Analytics leaders.
Speakers
- Tempest van Schaik PhDSr Machine Learning Engineer (Healthcare) at Microsoft
- Faizan JavedSenior Director of Search, Data Science and Analytics at Kaiser Permanente
- Colin (Lin) ChenExecutive Director at JPMorgan Chase & Co
- Javier OrracaData Scientist at Health Net
- Pragati AwasthiAVP Decision Science & Analytics at PNC
- Miriam FriedelDirector, Software Engineering - Center for Machine Learning at Capital One
- Ilya KatsovVP of Technology at Grid Dynamics
- Michael BergerVP, Chief Data & Analytics Officer and VP, Enterprise Data Science Center of Excellence at Mount Sinai Health System
- Jesse BishopEnterprise Account Executive at Dataiku
- Sandhya PrabhakaranResearch Scientist at Moffitt Cancer Center
Agenda
- 09:40 - 10:05 PDTMachine Learning in Computational Biology using single-cell RNA-seq data and spatial transcriptomic images
- 10:05 - 10:10 PDT5 min break
- 10:10 - 10:35 PDTHealthcare Finance Beyond Excel: R for Automation, Time Series Forecasting, and Interactive Reporting
- 10:35 - 10:40 PDT5 min break
- 10:40 - 11:05 PDTHow to create advanced analytics services for your company and business partners on top of CDP
- 11:05 - 11:10 PDT5 min break
- 11:10 - 11:35 PDTSearch & Recommender Systems for Healthcare
- 11:35 - 11:50 PDT15 min break
- 11:50 - 12:15 PDTData Science in the next Generation of Risk Management
- 12:15 - 12:20 PDT5 min break
- 12:20 - 12:45 PDTTechnical Debts in Machine Learning Systems
- 12:45 - 12:50 PDT5 min break
- 12:50 - 13:15 PDTJourney to AI at Scale: The View from the CDAO’s Desk
- 13:15 - 13:20 PDT5 min break
- 13:20 - 13:45 PDTResponsible AI in Health: From Principles to Practice
- 13:45 - 13:50 PDT5 min break
- 13:50 - 14:15 PDTStandardizing the Model Development Process
- 14:15 - 14:20 PDT5 min outro
About Data Points:
Data Points is an event series focusing on Data Science, Artificial Intelligence, and Machine Learning in enterprise applications. Join other senior practitioners and executives for immersive talks on use cases, trends, and the technical infrastructure powering the most sophisticated data practices. Learn from leaders in data who have implemented data practices at scale in a series of interactive presentations.
Participants
Topics
- Marketing spend optimization and attribution
- Customer analytics and personalization
- Fraud detection and risk scoring
- ML for quantitative equity portfolio management
- Price and promotion optimization
- Churn prevention
- AI/ML for IT Operations (AIOps)
- Data Science platforms and MLOps
- Deep learning for enterprise applications
- Reinforcement learning in personalization and trading
- Computer vision for digital experience platforms
- Data science platforms
- MLOps and AI productization
- Data platforms for self-service analytics
- Advanced data quality control
- Scalable data engineering
- Cloud data platforms