Name: MLOps community #5 (in-person | en personne)
Start: 2023-12-06T18:00:00-05:00
End: 2023-12-06T21:00:00-05:00
Location: Le Wagon Montréal Coding Bootcamp

Join us for a delightful evening of insightful discussions and valuable connections at our last meetup of the year! We're excited to announce that this event will be hosted at Le Wagon office in the Mile-End.

Get ready to delve into 2 engaging talks that explore the development of a Machine Learning (ML) project through the lens of product management, with a focus on MLOps.

Our speakers, Senior Product Managers will focus on how to lead applied ML for internal usecases and Introducing ML in Products.

This is a prime opportunity to gain valuable knowledge and connect with experts in the field. Don't miss out on this professional yet enjoyable gathering—it's the perfect way to wrap up the year on a high note!

For this event, we can host maximum 80 attendees so please register.

See you on December 6!

The MLOps Community

**AGENDA**
6:00 pm Doors open
6:20 pm Introduction
**6:30 pm How to lead applied ML for internal usecases, Ubisoft**
7:10 pm Break and networking
**7:30 pm Introducing ML in Products**
8:10 pm Final notes, break, and networking

Jean Philippe Petit-Frère

Thomas Meimoun

Jean-Michel Daignan

Vinh Nguyen

Stéphane Burwash

Montréal MLOps Community

Technology

New Technology

Data Science

Artificial Intelligence

Machine Learning

Data Engineering

Automated Machine Learning

Machine Learning Interpretability

AI/ML

**TALK #1**

**How to lead applied ML for internal usecases, Ubisoft**

In this talk, we will delve into the challenges and opportunities associated with managing Machine Learning (ML) projects through the lens of product management, with a specific focus on MLops and internal ML tools. From identifying stakeholders and partners to navigating the entire project lifecycle, we will explore strategies that strike a balance between the creative aspects of Research and Development (R&D) and the imperative for industrialization. Our discussion aims to bridge the gap between experimental and applied ML, offering insights into advocating for ML adoption and persuading internal stakeholders of its value. Join us for a concise and informative session tailored to optimizing your approach to ML project management, specifically tailored for internal use cases, focusing on MLops and the utilization of internal ML tools. 
 
**About Speakers**

**Yasna:** 
Yasna currently serves as a Strategic Product Manager at Ubisoft Montreal, where she focuses on developing internal ML tools for the company. In her role, she guides the vision and alignment of the ML platform, which is now utilized by more than 20 internal data scientists for the development and deployment of over 30 projects aimed at enhancing the player’s experience in the Ubisoft ecosystem. 
With a wealth of experience exceeding 10 years in product management, Yasna spent seven years at La Presse, where she led product management for the La Presse+ app. 
Beyond her professional endeavors, Yasna's personal interests include a passion for the arts, reflected in her membership on the Agora de la Danse board.

**Matthieu:** 
Matt currently holds the position of Senior Data Product Manager at Ubisoft Montreal, where his focus revolves around managing data products and refining processes. In his previous role as a Data Scientist, he played a pivotal part in improving in-game engagement through the implementation of personalized CRM programs and segmentations. 
Prior to his involvement in data-centric roles, Matt made meaningful contributions to the sports equipment industry as a mechanical engineer. His responsibilities extended globally, encompassing the oversight of product industrialization in Asia and the design of a biomechanics hockey motion capture Lab.

**TALK #2**

**Introducing ML in Products**  

During this presentation, acquire insights into the integration of machine learning features within a time management product. Explore the obstacles encountered during development and deployment of machine learning models within an established product with an existing customer base, including challenges related to industry resistance and privacy concerns. Uncover the methodologies employed to collect and leverage feedback for refining the models prior to their production release, and glean valuable lessons derived from this experiential journey. 
 
**About Speaker**

**Ruchi Bahadur:**
As a seasoned Senior Product Management leader, she boasts a wealth of expertise encompassing more than two decades in the realm of cloud SaaS products. Her professional journey includes a tenure as the Director of Product Management at Tempo Software, where she played a pivotal role in introducing and launching machine learning features and products. Originally rooted in software engineering, she transitioned her career trajectory towards business analysis and product management at an early stage. Her diverse background extends to consulting and implementing ERP solutions, with a focus on professional services automation and strategic portfolio management software markets. Beyond her professional pursuits, she finds enjoyment in activities such as listening to music, cooking, and travel. 

Yasna, Matthieu, Ruchi

MLOps community #5 (in-person | en personne)

Le Wagon Montréal Coding Bootcamp

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MLOps community #5 (in-person | en personne)

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