Leveraging Data Science for Financial Forecasting

Take a closer look at the use of data science in financial forecasting with European Association of Corporate Treasurers Award Winners JTI and learn how they improved forecast accuracy by 20%, while reducing their workload as much as 80%!

Tentative Schedule: (EST)

2:00pm: Intro
2:05pm: What To Expect of Machine Learning and AI in 2021 [Panel]
2:45pm: Q&A

Talk Abstract:

From leading-edge medical diagnostic systems to consumer electronics and “smart” home assistants, Artificial Intelligence is a critical technology that is changing how we live, work, and play. As we round out a turbulent 2020 and look towards the future, it’s undeniable that AI will continue to play a massive role in restructuring the way many of us handle business and communications. In this Virtual Meetup, we will be joined by a panel of Artificial Intelligence and Machine Learning specialists who will review the current state of the Artificial Intelligence industry in 2020 and forecast what to expect in the near future.

Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.

This technical webinar presented by research scientists at the Dataiku AI Lab will feature a discussion of the year's hottest topics in machine learning research and what's to come in 2021.

In this talk, Suresh Vadakath, financial services sales engineer at Dataiku, will demonstrate how he leverages Dataiku DSS to mine data using Principal Component Analysis (PCA) to evaluate equities for portfolio construction. From there, he will review how to balance risk versus return while being ESG-conscious in portfolio optimization.

Dataiku is a leading end-to-end, collaborative data science platform that enables technical and non-technical users to collaborate on building data science and analytics projects to aid data-driven decision making across the enterprise.

Lors de ce webinar, Léo Dreyfus-Schmidt (directeur de la recherche) et Vivien Tran-Thien (directeur pour les activités de conseil) de Dataiku feront un tour d’horizon de tendances émergentes en apprentissage automatique avec des applications intéressantes pour le monde de l’entreprise. Ils évoqueront des questions comme :

> Comment entraîner des modèles lorsqu’on dispose de peu de données ?
> Peut-on détecter et atténuer les biais algorithmiques ?
> Au-delà de formuler des prédictions, peut-on établir des liens de causalité ?
> Comment surveiller et maintenir les performances d’un modèle en production ?

In this talk, Suresh Vadakath, financial services sales engineer at Dataiku, will demonstrate how he leverages Dataiku DSS to mine data using Principal Component Analysis (PCA) to evaluate equities for portfolio construction. From there, he will review how to balance risk versus return while being ESG-conscious in portfolio optimization.

Dataiku is a leading end-to-end, collaborative data science platform that enables technical and non-technical users to collaborate on building data science and analytics projects to aid data-driven decision making across the enterprise.

Standardization and Improvements of Data Analytics Projects for Financial Institutions

Data Analytics is a hot topic for many financial institutions. Making the most of their data and becoming data driven companies is a strategic differentiator.

In this webinar, we identify practical difficulties in running relevant data analytics projects in financial institutions. Starting from typical projects (e.g. product pricing and behavioral modeling in banks and insurance), we explore some of these difficulties and provide practical solutions to implement a relevant data science pipe-line in financial institutions. We build a standardized approach along with the following steps:
-Business problem framing
-Data Management
-Modelling
-Deployment
-Monitoring

With some additional focus on the communication around data analytics projects and governance aspects. We advocate how data science platforms can help in robustifying this process, decreasing risks and increasing efficiency and added value of data analytics projects.

Speakers:
- Xavier Maréchal, CEO at Reacfin
- Samuel Mahy, Director at Reacfin
- Julien Antunes Mendes, Manager at Reacfin

Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Reacfin. They may contact you with information that could be of interest to you.

Tentative Schedule: (EST)

2:00pm: Dataiku x Bots & AI Intro
2:05pm: Navigating the Tricky Process of Becoming A Data Scientist w/ BMW
2:45pm: Q&A

Talk Abstract:

So you want to be a data scientist? Seems like everyone is typing that into Indeed. What does it actually mean to land your first role? How do you transition to data science from a different field? What does it take to be successful once you’re hired?
I’m not going to bore you with the tech stack requirements (although we’ll touch on this), but I’ll mainly focus on what I’ve learned though my own experience breaking into the field, and now as a hiring manager for data science interns.

Speaker Bio:

Dr. Natalie Morse is a data scientist at BMW in South Carolina, USA. She works within their innovation and research group to develop technology for the BMW Group. In addition to this role, she works as a graduate coach helping others navigate the tricky grad school world. Her goals are to bring more diverse voices to academia and tech.

Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.