Top Python Jobs in Toronto

Lead analytics for Zynga Poker by running A/B tests, building ETL pipelines and dashboards, analyzing player behavior, tuning game economy, and improving fraud/bad-actor models. Collaborate with product, design, and data science teams, contribute to AI/LLM initiatives, and maintain telemetry and BI tools to inform strategic decisions that impact millions of players.

Lead and execute complex threat intelligence investigations for live game services using OSINT, internal tools, and data analysis. Produce high-quality intelligence reports, support incident response, drive automation/tooling improvements, and maintain program reporting and threat monitoring.

The Senior Technical Artist will design, develop, and support tools for artists, innovate pipelines, and solve technical issues in a collaborative environment.

Design, develop, integrate, and commission real-time hardware-in-the-loop simulation test equipment. Create electronic schematics, develop LabVIEW/CVI control software, perform V&V, troubleshoot integrations, train users, and collaborate with cross-functional engineering teams to meet project, regulatory, and safety requirements.

Develop, test, and maintain CAM automation (HyperMill) workflows, macros, and tool libraries; align CAD/design libraries to support feature recognition; coordinate between Design, Machining, IT, and suppliers; standardize machining processes and tooling templates; provide training, documentation, and shop-floor support; analyze and improve automation performance.

The role involves designing and maintaining scalable backend systems, building data pipelines, creating an intuitive reporting UI, and mentoring junior engineers in a collaborative environment.

As a Product Strategy Analyst Manager, you'll lead analysis and strategy development, manage a team, and optimize customer products using data insights and technical tools.

The role involves helping modernize industries through IoT solutions, engaging with clients, managing implementations, and driving tech adoption. Significant pre-sales experience is required, coupled with a strong technical background in hardware and cloud applications.

Design and maintain ETL pipelines and Databricks Gold-layer tables; develop semantic layers, data dictionaries, and documentation for AI-driven BI; build dashboards and analyses to surface marketing and sales KPIs; perform ad-hoc deep dives; translate stakeholder requirements into scalable, analytics-ready data models; enable self-serve reporting and agentic AI workflows.

Serve as a client-facing Customer Success Manager for Economic Intelligence solutions: onboard and coach customers, deliver product demos and training, analyze macro/microeconomic trends, synthesize proprietary and third-party data into actionable insights, manage delivery of complex EI products, partner with product and sales, reduce churn, and support renewals and expansion across North America.

Client-facing Customer Success Manager for Mastercard Economic Intelligence: onboard and coach customers, run product demos and training, analyze macro/microeconomic trends, generate actionable insights, manage delivery of EI solutions, liaise with product and sales, reduce churn, support renewals and customer expansion, and collaborate with data scientists and consulting teams.

Research and implement macOS detection techniques and build them into production endpoint sensor features. Drive projects from concept through release, collaborate cross-functionally, troubleshoot issues, and apply secure, high-performance engineering practices using Swift/C++ and related tools.

Act as a hands-on technical lead designing and building fault-tolerant, cross-functional, multi-platform systems. Own architecture, improve developer tooling and engineering practices, mentor junior engineers, and contribute across the full software development lifecycle in a cloud-native environment.

Validate, reconcile, and analyze large datasets to identify data quality issues. Investigate anomalies, perform root-cause analysis, and recommend solutions. Work with business and technology stakeholders to define and execute validation activities, produce documentation and reports, and improve data quality processes and controls.

Own application-layer risk identification and remediation across consumer products and APIs. Build and operate AppSec tooling, Harden auth/authorization and GraphQL security, run HackerOne and offensive testing, lead threat modeling and security reviews, and build AI agents to automate triage and remediation while embedding secure-by-default practices into engineering workflows.

Design, operate, and improve cloud security for a multi-account AWS environment and Kubernetes clusters. Build detection, prevention, and automated remediation workflows, drive zero-trust access, shift-left security in pipelines, integrate cloud security tooling, mentor engineers, and partner with infrastructure teams on identity, networking, and secrets management.

As a Senior Associate, Data Analyst at Capital One, you will analyze datasets to support business strategies, communicate insights, and enhance decision-making through data visualization and stakeholder collaboration.

The Product Manager for Data Products at Capital One will drive the design and operationalization of data products, prioritizing long-term roadmaps, defining metrics-driven strategies, and collaborating across teams to enhance customer experiences.

As a Senior Software Engineer at BuildOps, you will design, build, and maintain product features across frontend and backend applications while mentoring others and improving system performance and reliability.

The Senior Site Reliability Engineer will design, optimize, and maintain MongoDB's multi-tenant distributed storage systems, ensuring reliability and operational safety while implementing automation solutions and participating in on-call support.

Join the Cloud Data Ingestion & Transformation team to design, build, and operate scalable data ingestion and transformation systems. Own end-to-end features (primarily back-end with front-end delivery), process very high data volumes, drive architectural decisions, and improve platform reliability and customer data integrations.

Develop and validate static and dynamic discrete-event/agent-based simulation models to improve throughput, de-bottleneck, and optimize material flow in automotive production. Collect and analyze process data, run what-if scenarios, perform statistical analyses and DOE, estimate resources and fleet needs, and provide data-driven recommendations while interacting with stakeholders and managing project data.

Lead end-to-end architecture and technical delivery of commercial insurance applications. Provide hands-on solution design, technical leadership, cloud-native microservices and API architectures, and embed Generative AI/LLM capabilities while ensuring security, data privacy, and responsible AI governance.

Lead a data science team to build scalable data pipelines, ML models, and tooling on AWS; operationalize and analyze large structured and unstructured datasets; collaborate across teams to source data and optimize business programs; hire and develop talent while evaluating new technologies for digital banking.

Design, develop, integrate, verify, and maintain cloud-native microservices across the OSS/BSS domain. Own features end-to-end, support CI/CD, monitoring, testing and production, collaborate with cross-functional international teams, drive process improvements, and engage in requirements and system architecture discussions.