Top Python Jobs in Toronto

The Senior Manager will oversee credit risk strategies, ensuring alignment with regulatory practices while providing analytical insights and influencing decision quality. Responsibilities include assessing credit proposals, conducting portfolio analytics, and mentoring team members.

The Director leads credit risk strategy oversight, optimizing governance and analytics to enhance retail credit strategy across the consumer lifecycle while ensuring compliance and capital efficiency.

As a Manager of Credit Risk Strategy Oversight, you will provide risk analytics and oversight for Canadian Retail lending, assessing proposals, monitoring portfolio performance, and enhancing credit decision-making.

Use advanced analytics, statistical testing, and machine learning to optimize onboarding, activation, and Next Best Action strategies. Build dashboards and automated reports, analyze campaigns and customer journeys, collaborate with cross-functional teams, and translate insights into actionable recommendations to improve engagement, profitability, and risk outcomes.

The Senior Governance & Control Analyst provides strategic oversight for Finance's risk management programs, ensures compliance with regulations, assesses internal controls, and fosters a risk-aware culture through collaboration and process improvements.

Design and implement scalable data ingestion and onboarding pipelines, build automation and Claude-powered tooling to reduce production MTTR, integrate third‑party sources (Veeva/Salesforce), design APIs and warehouse schemas, and collaborate cross-functionally to deliver production-grade data solutions on AWS and Snowflake.

Lead AI risk assessments, reviews, and monitoring to support AI governance at a financial institution. Evaluate internal and third-party AI solutions, maintain an enterprise AI inventory, analyze controls and risk metrics, build dashboards and reports, and provide quantitative and advisory support across stakeholders to enable responsible AI adoption and regulatory readiness.

Design, simulate and validate analog and mixed-signal IC blocks (PLLs, ADCs/DACs, filters, high-speed I/Os). Develop behavioral models (Verilog-A) for top-level simulation, perform process-corner simulations, automate flows with scripting, and validate silicon and system-level lab performance while collaborating with analog leads and multi-site teams.

Validate and research Generative AI and agentic systems, design and build enterprise AI applications (LLMs, RAG, agents), develop scalable software and automation, execute quantitative testing and validation, and maintain documentation to support governance and audit readiness.

Lead SIEM architecture, implementation, integration, and operations across modern platforms. Translate customer requirements into detection use cases and operational models, mentor teams, drive SOC transformation, integrate SIEM with SOAR/EDR, and present strategy to technical and executive audiences.

Lead retail and loyalty analytics by designing measurement frameworks, causal inference and experimental designs, building statistical, ML, and deep learning models, developing agentic AI and LLM solutions, and orchestrating scalable end-to-end analytical pipelines to improve customer engagement and marketing performance.

Build and maintain real-time and batch data ingestion and transformation pipelines using AWS and modern data tools. Design data models, consolidate sources into data lakes/warehouses, collaborate with engineers on data integrity, produce prototypes for unknown solutions, and support deployment of data models and dashboards for analytics and visualization.

Provide SRE expertise for Contact Centre application platforms: automate deployments, monitor and troubleshoot production systems, lead incident response and post-mortems, define observability and SLOs, participate in on-call rotation, and drive continuous improvement and AIOps automation to improve reliability and operational intelligence.

Lead retail and loyalty analytics by designing measurement frameworks, causal inference and experimental designs, building statistical, ML and deep learning models, and developing agentic AI solutions. Drive optimization and orchestration of end-to-end analytical pipelines, produce actionable insights for marketing and customer engagement, and present findings to business stakeholders.

Support credit risk teams by organizing electronic documents, automating IFRS 9 controls using AI, enabling and testing AI tools, documenting processes, and assisting with process improvements and data-driven risk analysis.

Founding engineering member building an AI-driven life-sciences SaaS platform. Own features end-to-end from design to production support, drive technical solutions, enforce best practices, perform expert code reviews, and mentor engineers to grow the team and deliver scalable, high-volume products.

Design, build, and productionize agentic systems: agent loops, orchestration, memory, tool integrations, and multi-agent workflows. Improve reliability by diagnosing emergent failure modes, instituting guardrails, and continuously evaluating agent behavior. Optimize tradeoffs among latency, quality, and token cost, and integrate agents with systems of record for business-grade production deployment.

Lead development of an AI-first enterprise SaaS platform: own feature implementation from design to production, collaborate on technical design, mentor engineers, perform expert code reviews, define engineering best practices, and support production systems using AI-assisted engineering tools.

Validate and review Generative AI and deep learning models, perform R&D on LLM evaluation and explainability, develop validation methodologies, apply statistical tests and benchmark models, and communicate findings to technical and non-technical stakeholders.

Support automation and transformation for Wealth Operations by building and maintaining automation (VBA/Python/RPA), migrating legacy code to Databricks/PySpark, developing low/no-code solutions (Power BI, Power Platform, Tableau), performing reporting and analytics, documenting processes, and enforcing data governance and risk controls.

Design, develop, evaluate, deploy, and monitor predictive and generative AI/ML solutions (including LLMs and agentic AI). Lead model assessment, vendor model evaluation, testing, validation, A/B experiments, and lifecycle management while ensuring Responsible AI, governance, performance, and clear communication with cross-functional stakeholders.

Design, build, and operate a scalable, secure cloud-native AI platform and services. Implement Akka-based event-driven microservices, MLOps pipelines, feature stores, model registries, orchestration, CI/CD, and APIs/SDKs. Optimize runtimes (CPU/GPU), ensure reliability, security, compliance, and support continuous/online learning and high-traffic agent interactions.

Lead design, build, and 운영 of CI/CD platform components: self-hosted GitHub Actions runners on GKE, ArgoCD GitOps topology, Helm charts, and Jenkins platform. Deliver self-service tooling and migrations, ensure pipeline reliability with Datadog and PagerDuty, manage artifacts and secrets, and collaborate globally to own architecture, incidents, and long-term maintenance.

Lead reliability, observability, and automation for a global AI platform. Define SLOs/SLIs, run on-call incident response, build CI/CD/GitOps and IaC (Terraform/Ansible), enable observability, enforce security and compliance, optimize scalability and cost, and productize the platform for developer experience and global regulatory requirements.

Design and deliver secure, scalable enterprise solutions. Partner with engineering, product, and business teams to create architecture artifacts, ADRs, POCs, and technical designs. Guide teams through project lifecycles, evaluate vendors, drive cloud adoption, AI integration, IaC, containers, and serverless patterns while ensuring security, compliance, and reusable architecture standards.