Top Data Science Jobs in Montreal

Use Coursera learner and product data to define and track KPIs, analyze consumer behavior, produce dashboards, partner with business leaders to inform consumer strategy, and present actionable insights to cross-functional teams to drive product and business decisions.

Founding Staff Data Scientist to build decision science from the ground up: design and deliver forecasting, optimization, experimentation, personalization, and recommendation systems; establish modeling standards, validation and deployment playbooks; mentor data scientists and integrate reusable decision workflows with the ML platform.

Data Scientist focused on fraud detection. Requires a Bachelor's degree, at least four years of relevant experience, and knowledge of French. Role emphasizes behavioral competencies (action orientation, customer focus, innovation, interpersonal skills) and is a hybrid position with competitive benefits.

Work on Alpha Science to source, clean, and build datasets; design data pipelines; perform statistical and ML analyses; build dashboards and reusable tools; communicate findings to deal teams; and leverage LLM-powered tools to support investment decision-making.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, design A/B and bandit experiments, develop pricing automation (DealBot) and monitoring for AI-driven rate recommendations, own ETL/analysis/visualization, and partner with Finance, Risk, Product, and GTM teams to operationalize pricing intelligence.

Use diverse data sources to evaluate product performance, build automated ETL/data workflows, design dashboards and KPIs, own data product quality, and provide analytical insights to guide product and business decisions while establishing monitoring frameworks and best practices.

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.

Lead growth-focused data science within a cross-functional squad: define KPIs, run experiments, perform causal inference and forecasting, build dashboards and self-serve tools, identify high-leverage opportunities across acquisition, activation, retention and monetization, and evangelize data-driven decision making to drive measurable business impact.

Lead high-impact analytical work partnering with senior executives to turn ambiguity into data-driven strategy. Design sophisticated analyses on large-scale data, mentor data science teams, build cross-functional trust, and deliver rigorous, decision-ready recommendations that influence long-term product and business strategy.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

Drive product and business analyses across Quora: design and evaluate experiments, build models and visualizations, analyze cross-product data to surface root causes, and partner with cross-functional teams to implement data-informed solutions and frameworks.

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.

Join a SignalFire talent network to be matched with VC-backed startups seeking Senior/Staff Data Scientists. Responsibilities include experimental design and analysis, predictive and causal modeling, productionizing models, building metrics and dashboards, advising product and business teams, mentoring other data scientists, and shaping data strategy and tooling at fast-moving startups.

Embedded on a core business team, define the right problems, build metrics and reports, run analyses and experiments, surface actionable insights, and drive data-informed decisions end-to-end across growth, product, AI, or partnerships.

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

Embedded data scientist owning analytics for a business unit: define problems, build metrics/reports/experiments, surface insights, and drive data-informed decisions across growth, product, AI, and partnerships.

Embed with a core business area to define problems, build metrics/reports, run analyses and experiments, and drive data-informed decisions end-to-end. Translate ambiguous questions into clear hypotheses, surface insights, and partner with product, growth, finance, and ops to execute recommendations and deliver measurable business impact.

Embedded on a central Data Science team, you will define problems, build metrics/reports, run analyses and experiments, surface insights, and drive decisions end-to-end for growth, product, AI/automation, or partnerships.

Embedded on a business unit, define analytic questions, build metrics/reports, run analyses and experiments, surface insights, and drive data-driven product, growth, AI, or partnership decisions end-to-end.

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

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Design and analyze experiments and causal studies, build retention measurement and predictive models, develop scalable PySpark/SQL data pipelines, create dashboards, and partner with product and growth teams to improve user engagement and retention.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

Lead growth-focused data science across cross-functional squads: design experiments, build models and dashboards, run causal analysis and forecasting, define KPIs, identify high-leverage opportunities, and drive data-informed product and marketing decisions to improve acquisition, retention, and monetization.

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