Top Data Science Jobs in Toronto

The Head of AI will define and execute an AI roadmap, lead research initiatives, mentor the AI team, and collaborate with senior leadership to enhance health technology.

Leads total fund data science, AI-enabled analytics, semantic modeling, governed data products, and investment reporting capabilities. Designs analytical models, ETL/ELT pipelines, semantic metric layers, data marts, and LLM/RAG interfaces across enterprise platforms. Provides technical oversight, governance, quality controls, stakeholder influence, and strategic delivery across Finance, Investments, Technology, and Data. Coaches colleagues and advances responsible AI adoption, reporting automation, investment insight generation, and operational efficiency.

Lead a team to deliver analytics solutions, transforming data into actionable insights, building AI/ML models, and collaborating across business units to drive analytics adoption.

Lead the development, validation, and maintenance of clinical data programming solutions for EDC/CDMS systems, vendor data, analytics, reports, integrations, and data transfers. Provide technical leadership across studies, serve as a programming subject matter expert, mentor programmers, support study teams, and drive automation and process improvements. Collaborate with data managers, biostatisticians, and project managers to ensure high-quality clinical trial data management solutions.

Develops, validates, and maintains clinical data programming solutions for CDMS and clinical trials, including eCRFs, edit checks, data validation outputs, reports, extracts, transfers, and vendor data programs. Collaborates with cross-functional clinical data teams, supports study setup and maintenance, mentors junior programmers, creates training materials, and improves technical systems and processes.

As a Senior/Staff Machine Learning Engineer, you will design scalable data pipelines, implement ML algorithms, and collaborate with engineers and Data Scientists to optimize the digital advertising platform.

Use data science, experimentation, forecasting, and analytical frameworks to improve Lyft’s airport marketplace. Analyze large datasets, define product health metrics, identify growth opportunities, recommend technical and product solutions, and measure feature impact. Collaborate with engineering, product, design, and other scientists while presenting actionable findings to senior leadership and cross-functional stakeholders.

Lead product strategy and execution for Clio's enterprise suite (Vincent and Operate). Define roadmaps, partner with Design, Engineering, Research, and Data Science, embed user research and data-informed decisions, and mentor other product managers. Drive AI-enabled product development, customer engagement, and cross-functional alignment to deliver enterprise-grade legal solutions.

As an Associate Product Manager at Switch, you will drive customer success, manage software implementation, and collaborate with engineers while shaping the product roadmap based on customer feedback and analytics.

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.

Leads MAU analytics and data science, managing decision scientists and data scientists while setting quality standards. Owns MAU driver modeling, forecasting, causal analysis, experimentation, and exploratory work supporting growth strategy. Establishes consistent analytical practices, partners with revenue, product, engineering, and data engineering leaders, and embeds the team in roadmap planning. Promotes AI-native workflows through coding agents, automation, and analytical tools while coaching team members into strategic advisors.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead Mozilla’s Marketing Data Science strategy and roadmap for Firefox. Drive attribution, ROI, campaign measurement, budget optimization, causal lift testing, brand impact analysis, retention and LTV modeling, audience segmentation, reporting infrastructure, dashboards, and scalable data tools. Mentor and develop team members, partner with cross-functional data science and marketing leaders, translate complex analyses into actionable recommendations, and evaluate emerging AI tools to improve workflows and business impact.

The Engineering Leader will oversee software and data teams, ensuring product delivery and operational excellence in robotics and IoT systems.

Lead and scale a product-focused data science organization to build production ML systems for personalization, recommendation, experimentation, and causal inference. Define strategy, partner with Product and Engineering, own end-to-end ML lifecycle, mentor the team, and measure product impact through robust analytics and monitoring.

Lead the development and delivery of AI-driven product capabilities, transforming data into actionable insights while mentoring a high-performing team of data scientists and engineers.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Design and maintain ETL/ELT pipelines and semantic/analytical data models; extend metric layers for BI and LLM/RAG-driven natural-language analytics; apply AI/ML and data-science techniques to produce trusted investment metrics, insights, and recommendations; embed data quality, lineage, and governance; collaborate with investment, finance, and technology stakeholders to prototype and productionize AI-enabled reporting solutions.