Top Python Jobs in Toronto

Provide technical and business support for Citi applications, troubleshoot and resolve production incidents, participate in releases and disaster recovery testing, maintain runbooks and documentation, perform RCAs and change control, liaise with stakeholders and technology partners, and support stability and efficiency initiatives.

Lead architecture and scaling of a live integration iPaaS for supply chain: harden platform for enterprise use, improve throughput, reliability, observability, tenant isolation, and mentor engineering while shipping zero-downtime changes.

Build and maintain backend services, APIs, and data models for a greenfield supply-chain platform. Implement business logic, ensure data integrity and API performance, manage relational schemas and migrations, write tests, integrate external systems, participate in design and code review, and help evolve backend architecture as the platform scales.

Support lab infrastructure by designing, building, modifying and maintaining test equipment and data acquisition systems. Troubleshoot electrical, pneumatic and hydraulic test systems, perform preventive maintenance and calibrations, assist staff with equipment setup, and pursue automation opportunities to increase throughput.

The Risk Operations Lead will manage KYC/B, AML, transaction monitoring, credit risk, and collections, enhancing risk functions and leading the team.

Lead design, build, and deploy large-scale search and information retrieval systems for legal and enterprise content. Own indexing, ingestion, ranking and re-ranking, semantic and hybrid retrieval, LLM-enhanced RAG architectures, evaluation frameworks, and production optimization. Mentor scientists, drive technical decisions, and partner with engineering to deliver reliable, scalable search services.

The role involves building AI inference systems, optimizing GPU performance, and developing benchmarking methodologies for large-scale deployments.

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.

Develop, validate, and deploy machine learning models for advertising guidance. Analyze large production datasets to generate insights, collaborate cross-functionally to integrate ML into products, publish research, and mentor junior researchers.

Lead GRC platform implementation and automation for ERM and Third-Party Risk Management across Post-Trade entities. Configure and deploy GRC tool workflows, support vendor risk assessments, deliver training and change management, assist regulatory reviews and incident reporting, and contribute to operational resilience, cyber risk, and business continuity initiatives.

Develop, maintain, and calibrate market risk and capital models (e.g., FRTB, VaR). Perform backtesting, ad-hoc testing, and model calibrations, collaborate with Technology, MRC, CMRM, and Model Validation, communicate model risk and assumptions, and contribute to group projects and methodology improvements.

Design, build, and maintain multi-cloud infrastructure (AWS/Azure/GCP); automate deployments with IaC and CI/CD; monitor and troubleshoot production systems; participate in on-call rotations; implement security and compliance controls; optimize performance, cost, and reliability; collaborate with DevOps, Security, and development teams to improve operational playbooks and tooling.

Lead global delivery of workflow, automation, and internal software solutions across 3–5 internal and third-party squads. Drive planning, capacity balancing, CI/CD, testing, release readiness, and operational support. Standardize delivery practices, enforce platform and architecture standards on Azure, Power Platform, and Microsoft Fabric, manage vendor SOWs, track delivery metrics, and communicate risks and status to technical and business stakeholders.

Design, build, and scale a big-data platform and microservices for event-driven, time-series, and analytical workloads. Lead architecture for streaming, processing, and storage (performance, cost, fault tolerance), develop REST APIs, integrate messaging and scalable datastores, ensure security/compliance, and champion AI-assisted developer tooling.

Develop, test, maintain, and support enterprise applications and ETL/data pipelines for AML and financial crime platforms. Assist with requirements analysis, data integration (Informatica/AWS Glue), scheduling/orchestration, incident resolution, documentation, Agile ceremonies, and on-call production support while ensuring security and compliance.

Lead full‑stack development of customer‑facing features using React/TypeScript and Python, design and deliver GenAI/LLM integrations (agentic workflows, MCP/A2A), set technical standards, collaborate with product/design/platform, drive execution, and mentor engineers to improve code quality and system reliability.

Lead IFRS 9 allowance reporting, governance, and regulatory submissions. Build automated analytics, dashboards, and reconciliations using Python/R/SQL and Power BI/Tableau. Maintain policies, controls, and audit-ready documentation; perform control testing, UAT, and stakeholder reporting. Drive process improvement, data modernization, and cross-functional initiatives with Risk, Finance, and Technology.

Lead commercial pricing strategy and a team of actuarial analysts to develop, govern, and enhance pricing models. Partner with Underwriting, Distribution, and Claims to deliver profitable pricing solutions, drive predictive modelling and portfolio optimization, and mentor staff while influencing strategic business decisions.

The Senior Full Stack Engineer will design and build core infrastructure for a logistics platform, focusing on backend systems, high-scale CRUD APIs, and real-time, event-driven architectures in a startup environment.

Lead product ownership and agile delivery for the QI Dashboard, a GAM-wide multi-asset risk and portfolio-construction analytics platform. Define roadmap, prioritize backlog, translate quant and risk needs into product increments, align stakeholders across multiple groups, partner on Databricks/Azure platform modernization, embed data governance and model-risk controls, and champion governed AI/ML enablement to deliver production-ready analytics and controls.

Support design, testing, and automation of Loyalty data pipelines and ETL processes. Perform UAT, post-launch validation, incident investigation, and stakeholder communications. Implement and test pipelines, monitor data quality, troubleshoot issues, and contribute to cross-source analytics projects under guidance of senior engineers.

Build scalable backend infrastructure, APIs, and data pipelines; develop React/Next.js frontends; implement production AI workflows; ensure reliability, observability, and performance; write well-tested code; collaborate with clients and contribute to architecture and design.

Perform actuarial analysis and reinsurance financial reporting, including monthly recoverables, treaty renewals, catastrophe bond planning, loss forecasting, and ad-hoc modeling. Maintain controls and governance (SOX/EUC), collaborate with pricing, claims, finance, auditors and brokers, and contribute to capability development through mentorship and training.

Support North America and GBX Finance by leading performance reporting, forecasting, variance analysis, and scenario modeling. Build dashboards, reusable SQL and automated workflows, and deliver executive-ready narratives and deep-dive analyses. Collaborate cross-functionally to link financial outcomes to operational drivers and recommend actions to grow GMV and improve buyer outcomes.