Presented by
MIAMI, SEPTEMBER 10-11
APPLYING AI & MACHINE LEARNING TO FINANCE, HEALTHCARE & Hospitality
The data science salon is a unique vertical focused conference which brings together specialists face-to-face to educate each other, illuminate best practices and innovate new solutions in a casual atmosphere with food, great coffee and entertainment.
About
Get access to powerful decisionmakers in data science in an intimate setting at Data Science Salon MIA, the only vertically-focused industry conference series around applications AI and Machine Learning in Finance, Hospitality, and Healthcare. Learn from practitioners, technical experts and executives how to solve real-world problems by harnessing disruptions in data, artificial intelligence, machine learning, and cutting-edge technologies. At DSS MIA, we connect you with our powerful community face-to-face and digitally – each ticket comes with one year of access to DSS Insider, the content repository for all Data Science Salons.
Data Science Salons are one or two- day events hosted at Blue Chip companies. Over 50% of our 200-500 attendees at each conference are data decision makers (Sr. Data Scientists and above). And we are the only data science conference with a gender balance in our speaking roster.
WHAT TO EXPECT
Data Science Salon Miami provides a common framework for thinking about what Machine Learning and AI means to the finance, healthcare and hospitality industries. The conference is organized into two days:
Day one consists of a mix of technical and conceptual hands-on workshops. You will walk away with actionable insights from those working on the frontlines of Machine Learning in the enterprise.
Day two consists of one general track covering: machine learning and AI applications in finance, healthcare and hospitality and specific break out sessions for finance and healthcare use cases.
Every major application of Machine Learning in finance, healthcare and hospitality will be covered.
A SAMPLE OF TOPICS COVERED
Putting ML Apps into production
PERSONALIZATION AT SCALE WITH AI
CLOUD AUTOMATION AND MACHINE LEARNING
Building ML pipelines to generate decisions faster
Natural Language Processing & Deep Learning
Engineering for Data Science
Scaling ML Production
Data Science Teams: Managing, Building, Collaboration
Improving Data Quality
Machine learning best practices
Data strategy and governance
Data ethics and bias
AND MORE!
data science execs and practitioners
Speakers
Days & tracks
Immersive experience
Meet our Speakers
Matt Denesuk
Sangeeta Krishnan
Laura Gabrysiak
Douglas Hamilton
Aaron Cheng
Jason Dolatshahi
Derek Plansky
Nathan Black
Connie Yee
Hong Wang
Moody Hadi
Leah Forkosh Kolben
Michael Zelenetz
Rochelle March
Catalina Arango
Manasi Vartak
Jeff Sharpe
Niraj Tank
Manojit Nand
Stanislaw Schmal
Joshua Malina
Surya Gupta
Carlos Ariza
Rupal Agrawal
David Whitney
Michelle Coca
Hemalatha B Raju
Charles Alcorn
Joseph Salvatore
media partners
Schedule
Tap on the Day 1 and Day 2 tabs to switch between the schedule for each day
Day 1 schedule
8:00 am – 8:50 am – Registration & Coffee
Coffee, Healthy Snacks, and Networking
8:50 am – 9:10 am – Introduction & Morning Meditation
9:10 am – 9:40 am – A Sustainable Agenda: Using ESG data to quantify company and portfolio impact
Moody Hadi, Group Manager – Financial Engineering at S&P Global Market Intelligence & Rochelle March, Senior Analyst at Trucost
9:45 am – 10:05 am – Processing Raw Financial Data: Challenges and Solutions
Connie Yee, Data Scientist at Bloomberg
10:10 am – 10:40 am – Improving Data Quality
Michelle Coca – AVP, Data Scientist, Business Intelligence & Analytics at Amerant Bank
10:45 am – 11:15 am – Re-Inventing Customer Engagement using Machine Learning
Laura Gabrysiak, Decision Analytics Architect at VISA
11:15 am – 11:35am – Coffee & Entertainment
Networking, Exhibitor Meet & Greet
11:35 am – 12:05 pm – Operationalize ML by Empowering People
Jeff Sharpe, Manager / Master Software Engineer at Capital One & Niraj Tank, Sr. Manager, Software Engineering at Capital One
12:10 pm – 12:30 pm – Cloud Automation and Machine Learning
Leah Forkosh Kolben, Co-founder & CTO at cnvrg.io
12:35 pm – 1:05 pm – AI and the Index Management Problem
Douglas Hamilton, Chief Data Scientist at NASDAQ’s Machine Intelligence Lab
1:05 pm – 2:00 – Lunch & Sponsor Table Crawl
Networking, Exhibitor Meet & Greet
2:00 pm – 2:45 pm – Panel – AI & ML Trends and Applications in Finance
Moody Hadi, Group Manager – Financial Engineering at S&P Global Market Intelligence
Jeff Sharpe, Manager/Master Software Engineer at Capital One
Laura Gabrysiak, Data Scientist at VISA
Joseph Salvatore, Director of Data Science at Idea Financial
2:50 pm – 3:20 pm – Fraud Prevention from the Ground Up
Jason Dolatshahi, Director of Data Science at Stash
3:25 pm – 3:55 pm – Privacy and Algorithmic Fairness
Manojit Nand, Senior Data Scientist at JPMorgan Chase & Co.
3:55 pm – 4:15 pm – Afternoon Coffee
Networking, Exhibitor Meet & Greet
4:15 pm – 4:45 pm – Time Series Analysis with Pandas
Joshua Malina, Senior Machine Learning Engineer at AMEX
4:50 pm – 5:10 – Being Agile when Developing AI Products
Manasi Vartak, Co-founder and CEO at Verta.AI
5:15 pm – 6:00 pm – DSSe Panel
Catalina Arango, Data Scientist at FPL
Michelle Coca, AVP, Data Scientist, Business Intelligence & Analytics at Amerant Bank
Hong Wang, Data Scientist at Independent Purchasing Cooperative
Rochelle March, Senior Analyst at Trucost
6:00 pm – 8:00 pm – Opening reception
Day 2 Schedule
8:00 am – 8:50 am – Registration & Coffee
Coffee, Healthy Snacks, and Networking
8:50 am – 9:10 am – Introduction & Morning Meditation
9:10 am – 9:40 am – Medical Content Management Concepts and A Roadmap to Support Clinical Decision Support Software in a Global Marketplace
Charles Alcorn, Head of Data Science at Roche Molecular Systems
9:45 am – 10:15 am – Keep your Customers Happy with Data Analytics
Stanislaw Schmal, Data Analytics & Strategy Lead at Lufthansa Industry Solutions
10:20 am – 10:50 am – People, Ships, & Destinations: How the Cruise Industry will Drive Enterprise AI Innovation, and Make People Happier
Matt Denesuk, SVP, Data Analytics & AI at Royal Caribbean Cruises Ltd.
10:55 am – 11:15 am – Scale Your Data Science Practice with Automation
Aaron Cheng, Vice President of Data Science and Solutions at dotData
11:15 am – 11:35am – Coffee & Entertainment
Networking, Exhibitor Meet & Greet
11:35 am – 12:05 pm – Rocky Journey to AI Adoption
Sangeeta Krishnan, Former Director, Enterprise Data Management and Strategy at Asembia
12:10 pm – 12:40 pm – How I Learned to Stop Worrying and Love Graph Databases
Michael Zelenetz, Analytics Project Leader at New York Presbyterian Hospital
12:45 pm – 1:15 pm – Deep Learning Applications in the Biosciences
David Whitney, Neural Research/Data Scientist at Max Planck Florida Institute for Neuroscience
1:15 pm – 2:15 – Lunch & Sponsor Table Crawl
Networking, Exhibitor Meet & Greet
2:15 pm – 2:35 pm – Human Machine Learning
Nathan Black, Chief Data Scientist at QuantHub
2:35 pm – 3:20 pm – Machine Learning Best Practices Panel
Derek Plansky (Moderator), Principal at Informatic Ideas
Carlos Ariza, Chief Data Scientist at Creative Artists Agency
Rupal Agrawal, AVP, Data Analytics and AI at Royal Caribbean Cruises Ltd.
Hemalatha B Raju, Ph.D., Lead Data Scientist at Biorasi
3:25 pm – 4:05 pm – A Product Development Approach to Improving Data Quality
Dalela Bharati, Product Owner- Data and Analytics at Booking.com
4:05 pm – 4:35 pm – Afternoon Coffee
Networking, Exhibitor Meet & Greet
4:35 pm – 4:55 pm – The Tabloid Proteome: Orthogonal use of public proteomics data to derive biologically related protein network
Surya Gupta, Postdoctoral Researcher at VIB-UGent
4:55 pm – 5:25 pm – AI and ML for the Data Quality of Clinical Trial Studies
Hemalatha B Raju, Ph.D., Lead Data Scientist at Biorasi
5:25 pm – 5:35 pm – Closing Remarks
attendees from
And many more!
DATE AND TIME
Sept 10 | 8:00 AM – 8:00 PM EST
Sept 11 | 8:00 AM – 6:00 PM EST