The data science salon is a unique vertical focused conference which grew into a diverse community of senior data science, machine learning and other technical specialists. We gather face-to-face and virtually to educate each other, illuminate best practices and innovate new solutions in a casual atmosphere.
Speakers

Jessica Stauth
Managing Director at Fidelity Labs

Devshree Golecha
Head of Analytics at TDECU

Ilya Katsov
Head of Data Science at Grid Dynamics

Jeff Sharpe
Sr Manager - Tech Lead, Enterprise Platform Products at CapitalOne

Abhishek Mehta
Director of Field Engineering at TigerGraph

Gaurav Deshpande
VP Marketing at TigerGraph

Thulasi Nambiar
Senior Manager, Marketing Data Science at Prosper

Sonali Syngal
Machine Learning Specialist at Mastercard

Brandy Walsh
Data Privacy Attorney at Acxiom

Kristie Wirth
Data Scientist at Zapier

Asaf Somekh
Co-Founder & CEO at Iguazio

Nick Brown
Senior Data Scientist at IHS Markit

Shruti Jadon
ML Software Engineer at Juniper Networks

Manasi Vartak
Founder and CEO at Verta

Laura Gabrysiak
Data Science Manager at Visa

Nikunj Aggarwal
Staff Software Engineer at Citizen

Alyssa Columbus
Datanaut at NASA

Vijay Pravin
Data Analytics Expert at Siemens AG (Germany)

Alina Petukhova
Product Lead at John Snow Labs

Subhabrata Majumdar
Senior Inventive Scientist at AT&T Labs Research

Julia Khan
Vice President of Analytics at SEMrush

Debasmita Das
Senior AI Specialist at Mastercard

About
Data Science Salon unites the brightest leaders in the finance, technology and travel across the nation in data science fields. We gather face-to-face and virtually to educate each other, illuminate best practices, and innovate new solutions. Data Science Salon | Finance, Technology & Travel is the only industry conference that brings together specialists in the finance, technology and travel data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Get the most current state of current industry trends and innovations in finance, technology and travel through DSS podcasts, exclusive content, Webinars and live Trainings. DSS also has an extensive on-demand video library of presentations from the top industry experts.

Schedule
(All times are US Eastern Time)
Tuesday, December 8 – Finance
12:00 pm – 12:10 pm – Introduction & Housekeeping
12:10 pm – 12:35 pm – Guided Meditation
1:15 pm – 1:45 pm – Empowering Organization Through Analytical Insights
Devshree Golecha – Head of Analytics at TDECU
1:50 pm – 2:10 pm – A Reinforcement Learning-based Architecture for Personalization Systems
Ilya Katsov – Head of Data Science at GridDynamics
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – Data Platforms and Why You Need One
Jeff Sharpe – Senior Manager, Tech Lead, Enterprise Platform Products at CapitalOne
3:35 pm – 4:00 pm – Building a data science team from ground up
Thulasi Nambiar – Senior Manager, Marketing Data Science at Prosper
4:05 pm – 4:25 pm – Server Failure Detection using Deep Learning: Moving from Research Datasets to Real-World Industry Server Data
4:25 pm – 4:30 pm – Wrap up
4:30 pm – 5:30 pm – Tuesdays Together
Wednesday, December 9 – Fin/Tech
11:30 pm – 12:30 pm – Virtual Coffee Chat
12:30 pm – 12:40 pm – Introduction & Housekeeping
12:40 pm – 1:10 pm – Data Privacy Law: An Unexpected Evolution
1:15 pm – 1:45 pm – Automating support ticket replies
Kristie Wirth – Data Scientist at Zapier
1:50 pm – 2:10 pm – Lessons Learned on Operationalizing Machine Learning at Scale
2:10 pm – 2:25 pm – 15 minute break
2:25 pm – 2:55 pm – How to train a Deep Learning Model in low data regime
3:00 pm – 3:20 pm – Reducing operational risk via model monitoring
3:55 pm – 4:10 pm – Wrap up
5.00 – 5.45 – Cooking Demonstration
Thursday, December 10 – Fin/Tech
12:30 pm – 12:40 pm – Introduction & Housekeeping
12:40 pm – 1:10 pm – How Open Access Information and Software Launches Innovation
1:15 pm – 1:45 pm – Insights on the advancements of Data Analytics in Mobility
Vijay Pravin – Data Analytics Expert at Siemens AG (Germany)
2:10 pm – 2:25 pm – 15 minute break
4:05 pm – 4:15 pm – Wrap up

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!