Top Data Science Jobs in Montreal

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.

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.

As a Data Scientist at Mistplay, you'll design and optimize the rewards economy, implement machine learning systems, and analyze strategies to enhance user engagement and business outcomes.

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.

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.

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.

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

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 Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

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.