Data Scientist

Overview

Groupe Dynamite Inc. (GDI) is a Montréal-based, public company of integrated omni-channel brands, designing and distributing accessible, trend-forward fashion for women since 1975.

Our mission of "Empowering YOU to be YOU, one outfit at a time" is brought to life through the GARAGE and DYNAMITE banners and represents the consumer-centric core of GDI's long-standing success as a leading retailer in North America.

Today, GDI operates nearly 300 stores across Canada and the United States, as well as shoppable brand experiences at Garageclothing.com and Dynamiteclothing.com.

Job Summary

We see our team as a R&D startup embedded within a larger organization. Our environment is dynamic, fuelled by constant brainstorming, technical discussions, and a love for "hacking." Our strength lies in the diverse technical backgrounds and cultures of our team members, which propels us through our daily work.

What truly distinguishes us is the tangible impact of our developments. Our models are deployed directly into production, significantly enhancing efficiency and fostering innovation for both our in-store and Head Office teams. These models are presented through internal tools and also directly to customers via our E-commerce platform.

As a member of the Data Scientist team, you will play a crucial role in leading, building, and advancing our demand forecasting, recommendation engines, and GenAI solutions. You will also be instrumental in establishing data science best practices across the organization.

Main Responsibilities

• Design and build advanced data models and scalable pipelines for production use;
• Collaborate with data scientists and engineers to solve real business problems using structured and unstructured data in the cloud;
• Write efficient, high-quality code to support Groupe Dynamite’s cloud-based solutions;
• Develop and deploy solutions using AWS, GCP, or Snowflake;
• Build and manage end-to-end ML pipelines, from data prep to training, deployment, and monitoring;
• Review code and models, support MLOps practices, and help maintain strong technical standards;
• Prototype new approaches in GenAI, forecasting, and recommender systems;
• Architect, implement, and deploy advanced data models and scalable data pipelines in production.

Qualifications

• A degree in Computer Science, Computer Engineering, or a related field;
• 3+ years of experience in a similar role, with a strong track record of delivering impact in production environments;
• Strong coding skills in Python and PySpark, with 3+ years of hands-on experience;
• Solid experience with both relational and NoSQL databases;
• Comfortable writing efficient queries for large structured and unstructured datasets;
• Hands-on experience building data pipelines in distributed/cloud environments;
• Experience in Data Science and Data Analytics, including statistical analysis, predictive modelling, and model evaluation;
• Practical experience with machine learning and MLOps;
• Well-versed in modern cloud technologies, such as Lambda functions and Glue jobs in AWS and Cloud functions in GCP;
• Strong analytical and problem-solving skills, attention to detail, critical thinking, and creativity;
• Ability to work effectively both independently and within a team;
• Strong communication skills and the ability to present technical content to non-technical audiences.

At GDI, You Will Be Part Of a Growing Organization That Understands The Importance Of Investing In People And Offers You

• A comprehensive compensation package that includes performance-driven bonuses;
• A group retirement savings program with employer matching;
• Flexible group insurance with personalized coverage that meets your needs;
• An employee discount at Garage and Dynamite;
• Exclusive private sample sales;
• A flexible vacation policy;
• And more!

GDI has been repeatedly voted one of Montréal’s Top Employers and one of Canada’s Top Employers for Young People.

Our promise…

No day will be like the last—we aim to be better today than we were yesterday. We are committed to employment equity.

Candidates that are retained will be called for an interview.