Top Data Science Jobs in Montreal

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 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.

Develop and deploy data science models, rules, and strategies to detect transactional fraud. Analyze fraud patterns, create predictive variables, test and monitor mitigation tools, and optimize analytics processes. Produce dashboards, visualizations, and reports while advising risk-management teams and business stakeholders. The role also involves researching industry trends and improving fraud detection best practices.

Own the end-to-end data science function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence leadership decisions. The role requires independently structuring ambiguous problems, using SQL or Python, communicating findings clearly, and driving measurable business outcomes.

Own the end-to-end analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to influence decisions and drive measurable outcomes. The role requires strong analytical ability, independent problem-solving, clear communication, and ownership of ambiguous initiatives.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to communicate findings, influence decisions, and drive measurable outcomes. The role requires strong analytical problem-solving, independent execution, and persuasive communication.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, pull and structure data, build reports, run analyses, design experiments, communicate insights, and drive recommendations and decisions with cross-functional stakeholders. Requires strong analytical thinking, independent execution, persuasive communication, and experience solving ambiguous problems in consulting, investment banking, or high-growth technology.

Own end-to-end data science for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires independent analytical execution, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives that drive measurable business outcomes.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate insights; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent data work, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives from end to end.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

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.

Embed with a business unit to define analytic problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end using SQL/Python.

Embedded in a core business area, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions to improve product, growth, AI/automation, or partnerships.

Embedded data scientist owning analytics end-to-end for a business unit: define problems and metrics, pull and analyze data, design experiments, build reports, surface insights, and drive recommendations that influence product, growth, and strategic decisions.

Embedded within a core business area, define analytics problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end with stakeholders.

Embed on a core business team to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve growth, product, AI/automation, or partnerships.

Embed within a core business area to define problems, build metrics, run analyses and experiments, create reports, surface insights, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

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 high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

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.

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.