Top Python Jobs in Toronto

Supports FX and interest-rate derivatives trading, including trade execution, booking, lifecycle management, hedge portfolio oversight, pricing, modeling, market analysis, reporting, and risk analytics. Maintains trading and market-data systems, reconciles records, resolves transaction issues, and improves workflows. The role collaborates with internal teams and external counterparties while developing expertise in derivatives, valuation, and financial markets.

Build and support machine learning pipelines and services across cloud and on-premise environments. Deploy, monitor, optimize, version, and retrain models using MLOps practices. Collaborate with ML engineers, data scientists, and product teams while working with AWS, Snowflake, data processing tools, and Linux systems. Contribute to scalable workflows, data privacy and compliance, code reviews, and knowledge sharing.

Own Braze as the technical and product subject matter expert, developing integrations, data models, pipelines, implementations, and migrations. Partner with CRM, Marketing, Product, and Engineering teams to deliver scalable personalized engagement solutions. Monitor platform performance and deliverability, support adjacent marketing platforms, and ensure security, privacy, consent, responsible gaming, documentation, and incident-response requirements are met.

Own and improve Elastic’s observability infrastructure across hosted cloud deployments. Responsibilities include Terraform-based infrastructure delivery, Python and Go development, production operations, incident response, on-call participation, RCA and postmortem writing, code and design reviews, mentoring, and improving operational documentation and processes. The role also involves operating Linux and containerized workloads, delivering complex projects independently, and maintaining secure, reliable platform infrastructure.

Supports life insurance and reinsurance pricing for RFPs through experience studies, assumption development, actuarial model development, cash flow projections, and research. Develops models using AXIS or R, prepares data documentation, analyzes mortality, morbidity, and longevity assumptions, and collaborates with pricing, underwriting, operations, reserving, marketing, and corporate actuarial teams. The role also supports client initiatives, business development, process improvements, and cross-functional projects.

Supports life insurance and reinsurance pricing for RFPs through experience studies, actuarial assumption development, model development, cashflow projections, and data analysis. Develops AXIS and R models, researches mortality and morbidity assumptions, prepares documentation, supports review committees, collaborates with underwriting and operations teams, and contributes to client initiatives, process improvements, and business development activities.

Design, build, and evolve highly concurrent backend services for ecobee’s Energy Control Platform. The role involves Go-based microservices, cloud development on GCP or AWS, database architecture, systems design, automated testing, CI/CD, reliability engineering, and production operations. The engineer will influence technical direction, adopt AI-assisted development practices, mentor teammates, collaborate with Product and engineering teams, and participate in an on-call rotation.

Own Jenkins-based RTL quality and release-promotion pipelines across lint, CDC, RDC, synthesis, and STA. Build QoR tracking, automated quality gates, waiver management, and evidence generation. Develop LLM-driven tooling to triage violations, create annotated pull requests, check spec-to-RTL consistency, and generate documentation. The role requires strong Python, hardware-flow knowledge, CI/CD expertise, and practical LLM integration experience. It is fully onsite Monday through Friday in the Bay Area, Vancouver, or Toronto.

Design, build, test, deploy, and monitor scalable software systems for client organizations. Collaborate with engineers, product managers, and designers across distributed systems, APIs, data, cloud, and user-facing applications. Use AI-assisted development and integrate AI or LLM capabilities into products while working directly with clients in a collaborative consulting environment.

Leads application solutions, product ownership, business systems analysis, integrations, and application support for wealth solutions and credit businesses. Manages ServiceNow incidents and SLAs, ETL/ELT workflows, data validation, documentation, reporting, and legacy migration to Snowflake. Partners with stakeholders to translate requirements into scalable technology solutions, supports users, and provides application expertise across asset management and insurance domains.

Leads application and data solution delivery for wealth solutions and credit businesses. Responsibilities include product ownership, business systems analysis, application support, integrations, ETL/ELT monitoring, data validation, documentation, incident response, automation, and migration to Snowflake. Partners with stakeholders to translate requirements into scalable technology solutions, supports users, produces business intelligence reporting, and ensures data governance, reliability, and compliance across insurance and asset management applications.

Build and operate investment data pipelines, integrations, and Snowflake platform capabilities supporting Aladdin and legacy systems. Responsibilities include ETL/ELT development, data modeling, orchestration, quality controls, lineage, testing, CI/CD, infrastructure as code, and production operability. The role also owns migration and conversion initiatives, resolves data issues, documents current and target-state platforms, and collaborates with investment, risk, finance, architecture, and delivery teams across Agile and waterfall environments.

Designs, deploys, and supports enterprise Azure cloud and DevOps solutions in a banking environment. Responsibilities include building CI/CD pipelines, managing Azure DevOps environments, automating infrastructure with Terraform and Bicep, supporting cloud services and container workloads, monitoring systems, troubleshooting incidents, and collaborating with technical and business stakeholders to deliver secure, reliable platforms.

Supports alternative investment clients through client implementations, investment performance measurement, attribution analysis, ex-post risk reporting, and GIPS compliance. Manages production processes, reviews calculations, validates data integrity, prepares client deliverables, and troubleshoots reporting issues. Collaborates with clients, product management, fund accounting, technical teams, and senior leadership. Also contributes to product testing, automation, process improvement, and analytical workflow enhancements.

Own digital, marketing, and e-commerce analytics projects covering subscription acquisition, retention, and expansion. Analyze and visualize data, create dashboards, identify meaningful insights, align metrics across teams, improve reporting, and communicate concise recommendations to support business decisions. Collaborate with global stakeholders, explore customer behavior and purchase funnel trends, and enable self-service data access and understanding.

Paid entry-level opportunities supporting the Toronto Blue Jays across scouting, player development, advance scouting, research and development, baseball systems, data engineering, app development, and performance science. Responsibilities may include organizing baseball data and video, operating technology, preparing reports, conducting analytics and research, developing internal applications and databases, and supporting team logistics. Candidates should demonstrate baseball knowledge, analytical and organizational ability, communication skills, and flexibility to work evenings, weekends, and holidays.

Own the full lifecycle of corporate audiovisual and unified communications systems across global offices. Administer Teams and Zoom Rooms, manage digital signage, design networked AV systems, support live events and broadcasts, troubleshoot complex audio/video/network issues, and coordinate vendors. Provide executive-facing support, mentor IT staff, maintain documentation, and assist with installations. Regular travel to Kitchener and periodic international travel are required.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, forecasting, targeting, and personalization. Collaborate with engineers and product teams, set modeling and productionization standards, mentor data scientists, guide architecture and experimentation, and apply cloud and MLOps best practices to drive measurable product and business impact.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Partner with Talent Acquisition and People teams to design and deliver People-platform integrations, data services, and AI-enabled automations. Build reusable integrations and platform patterns (Workday, Greenhouse), evaluate vendors, prototype AI solutions, and steward platform operations, governance, and security to scale People technology across the organization.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

Analyze digital campaign data, identify trends and insights, develop recurring reports, collect data from multiple sources, and present recommendations to stakeholders. The role manages reporting timelines, supports digital strategy planning, collaborates with industry partners, and helps improve measurement processes. Candidates should be skilled in relational databases, data visualization, analytics, data cleaning, and problem-solving, with media and advertising technology experience considered an advantage.

Diriger des enquêtes de cyberdéfense de la détection à la remédiation, mener des chasses aux menaces et concevoir des règles, tableaux de bord et playbooks. Étendre la couverture aux environnements Azure, GCP, Microsoft 365, conteneurs, pipelines CI/CD et applications cloud. Collaborer avec DevOps et l’ingénierie, participer aux exercices Purple et Red Team, exploiter le renseignement sur les menaces et évaluer des outils d’IA/ML pour améliorer la détection et le triage.

Leads cyber defense investigations from triage through remediation, conducts threat hunting, and develops detections, dashboards, playbooks, and SIEM/SOAR workflows. Secures Azure, GCP, Microsoft 365, endpoints, containers, CI/CD pipelines, and cloud-native applications. Partners with engineering teams, consumes threat intelligence, supports purple-team exercises, validates red-team coverage, and evaluates AI/ML tools for detection and alert triage.

Leads data engineering consulting engagements, serving as a subject matter expert and data architect. Designs scalable data environments, models, pipelines, integrations, warehouses, and visualizations while ensuring quality and governance. Leads architectural decisions, project delivery, technology strategy, and AI-augmented development practices. Mentors technical teams, collaborates with data scientists, analysts, clients, and stakeholders, and drives process improvements and innovation. The remote role may require infrequent travel to the United States.