Top Python Jobs in Toronto

Leads development and modernization of advanced credit risk models, including ECL, PD, LGD, EAD, and SICR models, using machine learning. Owns automation, MLOps, model monitoring, explainable AI, validation, and regulatory compliance. Partners with Credit Risk, Finance, Regulatory, MLOps, and IT teams, manages technical roadmaps, mentors multidisciplinary teams, and supports IFRS 9 provisioning and capital planning.

Supervises income and entitlement processing within brokerage operations, including dividends, distributions, reconciliations, reporting, escalations, vendor relationships, and risk mitigation. Leads analysts, ensures accurate and timely back-office processing, documents procedures, supports client inquiries, and coordinates cross-functional projects. The role also drives automation using n8n, SQL, Python, and AI, while supporting staffing, training, workflow allocation, and operational improvements.

Owns and modernizes CI/CD pipelines for brokerage systems across C++, .NET, Node.js, Python, and Angular applications. Responsibilities include build optimization, artifact management, micro-frontend delivery, Apigee and GCP release automation, Terraform infrastructure, DevSecOps quality gates, AI-assisted code review, testing dashboards, compliance controls, and DORA metric improvement.

Leads cybersecurity incident response, threat hunting, alert development, detection engineering, forensic investigations, containment, eradication, and recovery. Mentors SOC personnel, manages high-severity incidents, develops playbooks and detection strategies, conducts tabletop exercises, coordinates with internal teams and vendors, reports SOC metrics, and presents findings to leadership. The role includes on-call rotations and requires expertise with SIEM, EDR, SOAR, cloud security, forensic triage, and security automation.

Build and maintain Python, SQL, workflow, automation, dashboard, and AI-enabled tools for Enterprise Compliance. Identify manual and data-intensive processes, support complaint investigations, extract and analyze data, develop reporting, and ensure privacy, security, legal, records management, and compliance controls. Partner with stakeholders, document solutions, train users, manage projects autonomously, and communicate technical concepts to nontechnical colleagues. Regulatory and financial services knowledge will be developed on the job.

Leads cybersecurity incident response and threat-hunting activities, including alert triage, complex investigations, containment, eradication, recovery, detection-rule tuning, and forensic analysis. Uses SIEM and EDR tools such as Elastic Security and CrowdStrike Falcon, develops playbooks and SOC processes, coordinates with internal teams and vendors, mentors junior analysts, reports operational metrics, and participates in on-call rotations and tabletop exercises.

The Senior Quality Assurance Engineer designs and executes manual and automated testing for APIs, backend applications, microservices, and high-volume transactions. Responsibilities include developing test strategies and regression suites, configuring test environments, managing defects, analyzing root causes, reporting risks, supporting sprint planning, and improving QA processes. The role requires Python or JavaScript/TypeScript, Linux, API testing, SQL, cloud technologies, performance testing, and modern development pipelines.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Lead technical strategy and pre-sales engagement for large enterprise accounts, guiding customers through Databricks adoption and data-driven transformation. Build executive relationships, present technical value propositions, coordinate virtual teams, develop technical champions, align account strategies, and mentor colleagues. The role requires expertise in big data, data science, cloud, ML and AI use cases, plus production programming experience in Python, R, Scala, or Java.

Lead technical strategy and adoption of Databricks solutions for large financial services and insurance accounts. Partner with enterprise sales teams, executives, influencers, and technical resources to drive data and AI transformation, build technical champions, guide evaluations, and align solutions with business outcomes. The role requires expertise in big data, data science, cloud platforms, machine learning, programming, value selling, and technical leadership across global enterprise accounts.

Build and operate scalable full-stack software and AI-powered products for IoT-driven physical operations. Responsibilities include defining technical strategy, developing backend services, APIs, frontend and potentially mobile features, transforming AI capabilities into customer products, partnering across functions, leading complex projects, mentoring engineers, and improving engineering standards.

Lead product analytics for content supply and understanding, defining KPIs, measurement strategies, dashboards, experiments, and data-quality standards. Analyze content gaps, metadata quality, discovery, engagement, opportunity sizing, and ROI. Partner with Product, Engineering, Data Science, and executives to guide strategy and roadmaps, investigate anomalies, validate AI-assisted analysis, communicate findings, and mentor analysts.

Develop and validate predictive credit risk models using large retail lending datasets, advanced statistical methods, and machine learning. Build dashboards highlighting expected credit losses and risk drivers, support model validation and compliance, and provide analytical insights to retail risk, finance, and product stakeholders. The role also involves data mining, portfolio segmentation, model documentation, and decision support for lending growth, profitability, and risk management.

Provides independent second-line oversight and effective challenge of retail credit strategies, policies, models, and portfolio decisions. Performs portfolio analytics, monitors emerging risks, evaluates regulatory compliance, supports audits and examinations, and advises senior stakeholders on risk-adjusted returns and mitigation. Leads governance documentation, cross-functional collaboration, analyst development, work allocation, quality review, and capability building.

Develops and deploys advanced machine learning solutions and enterprise analytics using Python, PySpark, PyTorch, SQL, cloud platforms, deep learning, and large language models. Partners with business owners, engineers, data scientists, and modelers to translate business objectives into technical solutions, generate insights, and deliver production AI/ML systems. Provides technical leadership, stakeholder communication, risk governance, research, mentorship, and continuous improvement across complex initiatives.

Validates retail credit risk, capital, stress-testing, and other financial models. Develops independent statistical and machine-learning benchmarks, evaluates model assumptions and implementation accuracy, documents validation results and limitations, and recommends model approval or improvement. The role also collaborates with model development teams and vendors, monitors evolving regulatory and industry requirements, and supports effective risk-model governance.

Design, build, and operate highly available cloud and hybrid networks across GCP, Azure, and AWS. Manage connectivity, routing, VPNs, firewalls, load balancing, DNS, Kubernetes networking, and infrastructure as code with Terraform. Troubleshoot performance and connectivity issues, support zero-trust access, participate in on-call operations, and plan capacity, disaster recovery, and network costs.

Design and build hyperscale observability infrastructure for metrics, logs, and traces. Develop fault-tolerant, high-throughput distributed services using Golang or Python; operate Kubernetes-based systems; improve resilience through autoscaling and self-healing; and partner with SREs and platform teams on reliability, incident response, architecture reviews, and production operations. The role includes on-call participation and work with technologies such as Prometheus, OpenTelemetry, ClickHouse, and Grafana.

Develops forecasting, regression, statistical, machine learning, and AI solutions for banking operations. Responsibilities include analyzing complex datasets, building predictive and time-series models, automating reporting, creating dashboards, communicating insights, and partnering with operations, risk, product, data engineering, and technology teams. The role also supports agentic AI initiatives and helps business partners adopt new analytics capabilities.

Analyzes, monitors, and reports counterparty credit risk exposures against approved limits. Investigates and escalates credit excesses, ensures accurate risk measurement and reporting, supports policy and infrastructure changes, maintains internal controls, and performs ad hoc exposure analysis. The role partners with credit risk, market risk, front-office, audit, technology, and other stakeholders while supporting process improvements and operational risk management.

Design, operate, and improve foundational storage systems supporting Sentry’s products. Build storage APIs and abstractions, solve distributed consistency and scaling challenges, plan migrations, optimize performance and cost, and collaborate with platform and product engineering teams. Develop primarily in Rust and Python, create advanced reliability tests, maintain observability and availability SLOs, respond to incidents, document technical decisions, and participate in on-call rotation.

Own the production deployment of neural and generative models for Waabi’s multi-sensor simulator. Responsibilities include optimizing models with compilation, quantization, mixed precision, CUDA, and custom kernels; building numerical parity benchmarks; developing model export, versioning, registry, and build tooling; collaborating with research teams; and managing GPU workloads in cloud environments.

Designs and owns scalable analytics data models, pipelines, semantic layers, and data quality practices. Partners with engineering, product, AI, and business stakeholders to translate ambiguous needs into reliable data solutions. Responsibilities include dimensional modeling, transformation workflows, observability, documentation, governance, lineage, warehouse optimization, and self-service analytics enablement using modern cloud data platforms.

Supports Sales and Marketing through data analysis, reporting, dashboard development, programming, automation, and AI-enabled solutions. The role extracts and validates data, analyzes performance, defines KPIs, develops Power BI visualizations, investigates discrepancies, and translates findings into actionable business recommendations. It also partners with cross-functional stakeholders, supports dealer and marketing programs, automates processes, and improves data quality and operational efficiency.

Supports the design, development, testing, integration, and maintenance of star tracker optical systems. Responsibilities include developing production and R&D test setups, analyzing performance data, supporting root-cause investigations and non-conformance disposition, assisting with assembly and integration, and responding to customer inquiries.