Top Data Science Jobs in Montreal

The Data Scientist will analyze customer behavior, optimize product initiatives, and collaborate with cross-functional teams to drive revenue growth.

Partner with Marketing leadership to design measurement frameworks, run and analyze experiments, evaluate campaign incrementality, build dashboards and automated reports, ensure data quality, and deliver actionable insights to optimize marketing performance.

Lead R&D data science projects from experimentation to production, using PySpark/Scala and ML to analyze listener behavior, develop explainable models, collaborate cross-functionally, document results, and present findings to stakeholders.

The Data Scientist will develop data labeling strategies, optimize datasets for LLMs, analyze data quality, and collaborate with engineering on data processing pipelines.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

As a Data Scientist II, you will develop innovative solutions using machine learning, transform data into actionable insights, and collaborate across departments to enhance data-driven decision making.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Perform product analytics by analyzing large datasets, running A/B tests, building dashboards, applying statistical methods and ML for forecasting and segmentation, and communicating insights to product, sales, and customers to drive adoption and product improvements.

Embedded within a core business area, you will define analytical problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-driven recommendations end-to-end to influence product, growth, AI, or partnerships.

Embed within a core business area to own analytics end-to-end: define problems, build metrics/reports/experiments, analyze data, surface insights, and drive outcome-focused recommendations with stakeholders to improve growth, product, AI/automation, or partnerships.

Embed on a core business team to define problems, build metrics, run analyses and experiments, and drive data-informed product, growth, AI, or partnership decisions end-to-end. Surface insights, recommend actions, and own execution to improve key business metrics.

Embed with a business unit to define problems, build metrics and analyses, run experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embedded on a core business team, the Data Scientist defines problems, builds metrics and reports, runs analyses and experiments, and translates insights into executable recommendations to drive growth, product, AI/automation, or partnership outcomes.

Embed within a business unit to define problems, build metrics/reports/experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Design and deploy predictive models and segmentations using statistical and ML/AI methods. Prepare, clean, and feature-engineer data from warehouses, develop and operationalize models, create visualizations and presentations, document rules, and advise stakeholders to inform business decisions and improve data management tools.

As a Data Scientist at Gameloft, you will analyze large player datasets and implement machine learning models to drive game revenue. Responsibilities include feature engineering, prototyping ML models, and contributing to experimental designs.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

Lead a team of Data Scientists and Data Engineers to create data assets and insights, impacting game development and business strategy through analytics.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

The Data Scientist II will work with sports tracking data to build models and analyses for NHL and NBA organizations, focusing on data transformation and metrics development.

Build, deploy, and iterate predictive models and real-time scoring pipelines using behavioral and clickstream data to improve lead quality and campaign optimization. Collaborate with marketing, media buying, and analytics teams to translate business needs into hypotheses, perform exploratory analysis, monitor model performance, and communicate statistically rigorous insights to non-technical stakeholders.

Lead development and vision for the Client Journey Database (CJDB), make data products AI-ready, collaborate with stakeholders, build user-friendly tools, transform complex data into actionable insights, validate analytic approaches, promote data governance and a data-centric culture, and tackle data engineering and IA engineering challenges.

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

The Senior Data Scientist will lead data science strategy, develop models for lead qualification, fraud detection, and underwriting, and collaborate with product and engineering to enhance financial products.