Top Python Jobs in Toronto

Lead client-facing Commerce Analytics and Insights engagements: translate client goals into analytic scopes and execution plans, align stakeholders, connect needs to Criteo products, and drive delivery and scalable solutions. Act as strategic partner across commercial, product, data science, and analytics teams to prioritize work, ensure methodological feasibility, and convert recurring asks into repeatable frameworks or product feedback.

Lead the Cloud Operations team to design, deploy, secure, monitor, and maintain reliable cloud environments (Azure/AWS). Manage production deployments, CI/CD/IaC, APM, SOC2 compliance, incident handling, automation, and process improvement while mentoring staff and collaborating with R&D and leadership.

Design, prototype, and deploy advanced visualizations and machine learning models for segmentation, personalization, churn prediction, LTV forecasting, and marketing optimization. Partner with stakeholders to define problems, lead end-to-end data science projects, adopt emerging tools, improve analytics workflows, communicate insights to varied audiences, and mentor peers to set technical standards.

Design, build and optimize BI assets (QuickSight dashboards, semantic data models) on SQL datasets. Develop and maintain data pipelines, perform SQL tuning, ensure data quality and governance, and support the web presentation layer. Collaborate with business partners to deliver accurate, performant, secure reporting and analytics.

Lead design, development, and deployment of data science and GenAI solutions. Translate business goals into ML problems, engineer features, train/evaluate models and LLMs, build RAG/agent systems, work with vector DBs, mentor juniors, and communicate results to stakeholders.

Lead quality improvement and root cause analysis in coating/manufacturing, maintain PFMEA and control plans, implement digital quality systems, perform capability studies (Cp/Cpk/Pp/Ppk), ensure compliance to QMS and ISO/IATF standards, support audits, supplier and customer quality, and provide hands-on production troubleshooting.

Build and own end-to-end ML features for an agent management platform in healthcare: design data models, build pipelines and backend services, integrate frontend when needed, ground and evaluate agent behavior using clinical data (FHIR/HL7), prototype with hospital partners, and create novel solutions for agent observability, evaluation, and continuous improvement.

Develop, modify, test, debug and document pricing and underwriting algorithms and tables. Collaborate with Actuarial, Underwriting and IT teams, assess impact of changes, deliver project tasks on schedule, recommend process improvements, and ensure data accuracy and maintainability.

Administer and optimize Microsoft Fabric and Power BI environments; manage Azure data ecosystem (Synapse, Azure services); enforce identity and data governance via Microsoft Entra ID and Purview; implement RBAC and security/compliance controls; develop and troubleshoot with DAX, T-SQL, or Python; perform enterprise platform troubleshooting and optimization.

Lead product strategy and roadmap for high-throughput data ingestion, Databricks/Medallion lakehouse analytics, and FHIR-native MDM. Define streaming/batch ingestion, identity resolution, error remediation, DLQ replay, and APIs to produce a scalable, fault-tolerant data platform for clinical records and analytics.

Operate, monitor, and optimize large-scale AI compute clusters built on the Wafer-Scale Engine. Develop and own software for cluster operations (monitoring, automation, APIs, dashboards), deploy and debug Docker-based services, troubleshoot distributed systems, maximize compute capacity, and participate in a 24/7 on-call rotation while collaborating cross-functionally to improve operational visibility and reliability.

Design, develop and lead automation and analytics solutions using low/no-code tools, ETL, BI and cloud platforms. Translate business requirements into technical designs, provide senior technical consultation, mentor junior staff, and drive automation and process improvements to improve operational efficiency.

Design, build, and maintain enterprise BI infrastructure and services. Develop and optimize back-end systems, dashboards, reports, and ETL workflows. Collaborate on infrastructure design, automate processes, troubleshoot production issues, and evaluate emerging BI and cloud technologies to support business intelligence needs.

Design and implement state-of-the-art models for ranking, recommendations, personalization, and pricing. Develop core ML platform and feature engineering systems (Zipline). Productionize research models by building ETL/ELT workflows, inference pipelines, and deployment automation. Implement MLOps, model serving, monitoring, observability, and optimize model performance SLOs and system costs.

Design, build, and productionize ML models and infrastructure for ranking, recommendations, personalization, and pricing. Develop feature engineering systems, ETL/ELT and inference pipelines, deploy and monitor models, ensure observability, performance SLOs, cost optimization, and MLOps automation.

eBay is hiring ML Scientists to design state-of-the-art ranking, recommendation, personalization, and pricing models, and ML Engineers to productionize models by building ETL/ELT workflows, inference pipelines, MLOps infrastructure, deployment automation, monitoring, and cost/ performance optimization. Both roles contribute to feature engineering, model serving, observability, and maintaining production ML platform components like Zipline.

eBay seeks ML Scientists and ML Engineers to design ranking, recommendation, personalization, and pricing models and to build production ML infrastructure. Responsibilities include model research, feature engineering (Zipline), productionization, ETL/ELT pipelines, model serving, monitoring, deployment automation, observability, and cost and performance optimization.

eBay is hiring ML Scientists and ML Engineers to design advanced models for ranking, recommendations, personalization, and pricing, and to productionize those models. Responsibilities include feature engineering with Zipline, building ETL/ELT and inference pipelines, MLOps, model serving, monitoring, deployment automation, and cost/performance optimization.

eBay is hiring ML Scientists and ML Engineers to design ranking, recommendation, personalization, and pricing models, develop feature engineering and Zipline-based ML platforms, and productionize models via ETL/ELT pipelines, deployment automation, monitoring, and cost/performance optimization.

Lead design and development of enterprise full‑stack applications using Python and React. Architect scalable REST APIs and microservices, work with SQL/NoSQL databases, deploy on cloud (AWS/Azure) with Docker/Kubernetes, maintain CI/CD pipelines, optimize performance, mentor developers, and collaborate with cross‑functional teams in an Agile environment.

Maintain and advance CIBC's exposure management ecosystem by ensuring platform reliability, scanning coverage, data ingestion, and data quality. Build and maintain integrations across assets, identity, cloud, and network sources, troubleshoot application issues, collaborate with cross-functional teams, and apply AI/automation to improve operational processes and platform capabilities.

Lead and administer on-premises and Azure SQL Server environments including deployment, migration, backups, replication, monitoring, performance tuning, security, troubleshooting, and disaster recovery. Automate DBA tasks, support change deployments, provide after-hours support, and collaborate with architects, developers, and application support teams to ensure availability and reliability.

Design, develop, and deliver full-stack features for e-commerce apps. Convert user feedback into product improvements, maintain and optimize high-traffic back-end systems, perform code and design reviews, and improve development and deployment processes.

Deliver and implement ServiceNow solutions (ITSM/ITOM), configure and integrate products, develop custom scripts, produce technical documentation, run workshops/POCs, and support sales and service growth. Work is consultative with customer-facing delivery, both remote and on-premise.

Deliver ServiceNow consulting engagements focused on ITOM (discovery, service mapping, CMDB, event management); develop custom scripts and integrations; produce technical documentation; support services growth; deliver onsite or remote and educate customers on ITOM/ITIL practices.