Top Python Jobs in Toronto

Lead analytics-driven revenue growth through client acquisition, lifecycle management, lead optimization, and campaign enablement. Translate data and market insights into prioritized strategies, build tracking and KPI frameworks, enable AI-enabled insights, design and test programs, optimize campaigns and journeys, and lead a team to deliver analytics, reporting, governance, and stakeholder-aligned growth outcomes.

Partner with stakeholders to translate business strategy into digital and AI initiatives: analyze data, design agentic AI workflows, build prototypes/POCs, support agile delivery, and enable adoption of new digital tools to drive strategic outcomes.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

Lead implementation projects focused on data management and integration for financial institutions. Define solutions using SimCorp One®, liaise with clients, coordinate with project managers, mentor colleagues, improve implementation best practices, and ensure delivery of data integration and performance improvements.

Support daily market reference data operations for investment systems: investigate and resolve data exceptions, validate pricing and valuations, document procedures, support change initiatives and testing, and collaborate with stakeholders to improve data quality and controls.

Design, build, and maintain scalable data platforms and pipelines using Azure Fabric, Databricks, and Snowflake. Optimize ETL/ELT workflows, ensure data security and compliance, perform data modeling and transformations, and collaborate with analysts, scientists, and stakeholders to deliver reliable, high-performance data solutions.

Lead architecture and build an internal, scalable evaluation platform for LLMs and agentic systems. Own orchestration, automation, and observability to turn manual prompt iteration into reproducible evaluation loops. Act as AI technical lead for squads, define quality metrics, mentor engineers, and collaborate with infrastructure teams to run large-scale evaluations and agent simulations.

Lead and grow the hardware test engineering team to deliver test infrastructure, procedures, automation, and evidence packages for satellite hardware. Oversee validation, qualification, production test strategy, reliability campaigns, cross-functional alignment, and scalable processes while coaching engineers and advancing test automation, data systems, and facility capability.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Lead development, validation, automation and governance of Canadian consumer credit risk reporting. Design and deliver regular and ad-hoc reports for management and regulators, coordinate data integration and controls, support audits, advise business stakeholders, and continuously improve reporting processes and automation.

The Lead Sales Analyst will analyze sales data, optimize revenue strategies, build reporting tools, and influence decisions on sales performance and strategy.

The role involves operating and scaling Kong's SaaS platform, building automated infrastructure, optimizing multi-region data layers, enhancing observability, and ensuring reliability across services.

Lead electrical design from concept through mass production, ensuring manufacturability, reliability, compliance, and cost targets. Drive schematic and PCB design, RF and analog development, production test strategy, supplier/component selection, DfX processes, and cross-functional project leadership across EVT/DVT/PVT/MP phases.

The Senior Software Engineer will architect and deliver a CRM and data platform, automate workflows, and integrate data across systems to support growth in the firm.

Embed with application teams to lead cloud-native modernization on AWS, drive AI-assisted SDLC adoption, implement IaC and CI/CD (Terraform, GitHub/GitLab), solve integration challenges, and upskill teams while enforcing engineering standards.

The Senior Full-Stack Engineer for AI Platform will design and implement frontend and backend components, ensuring high-quality code, system performance, and collaboration across teams. The role emphasizes delivery, architecture, and testing discipline in a fast-paced environment.

The Senior Backend Engineer will design and implement backend services using TypeScript and Python, focusing on NestJS and FastAPI, and contribute to AI-related workflows and document processing.

The AVP, Lead AI Engineer will architect and deliver production LLM systems, oversee a team of engineers, and ensure high performance coding in AI applications.

The Machine Learning Engineer will create scalable ML systems, build production data pipelines, and ensure robust deployment and monitoring of solutions.

Seeking an experienced Data Engineer to design and maintain data pipelines and infrastructure, collaborating with data scientists and stakeholders.

The Machine Learning Engineer II crafts and deploys advanced AI solutions leveraging machine learning technologies, focusing on real-world applications and scalable systems. Responsibilities include coding for model deployment, managing large datasets, and working within a collaborative AI team.

The Treasury Manager will manage liquidity risk frameworks and systems while collaborating with various departments to implement new products and ensure compliance with regulatory requirements.

The Senior Actuarial Analyst will develop pricing methodologies, support rate filings, perform data analyses, and collaborate with teams to enhance pricing strategies for personal auto insurance.

The Senior Analyst will develop vertical-specific advertising solutions, work with cross-functional teams, and analyze data to drive marketing performance improvements.