Top Python Jobs in Toronto

Develop investment analytics that improve investment manager effectiveness and decision-making. Research analytic methodologies, build proofs of concept, work with investment teams and leadership, and productionalize solutions with platform teams. Analyze financial datasets across performance, risk, attribution, liquidity, ESG, fees, and trading. Apply AI to financial modeling, anomaly detection, and natural-language data queries while resolving complex issues and communicating technical concepts clearly.

Manage the analytics production pipeline from data ingestion through calculation and distribution. Develop scalable investment analytics solutions covering performance, attribution, risk, exposure, and investment models. Maintain dashboards and semantic layers supporting natural language queries, enhance proprietary and third-party analytics tools, resolve complex methodology issues, and improve workflows. Translate technical concepts for investment stakeholders while identifying process risks and implementing technology-driven efficiencies.

Build and maintain BI dashboards, reporting tools, and automated data workflows. Analyze customer behavior, funnels, retention, engagement, and product adoption to deliver actionable insights across Product, Operations, Marketing, Finance, and Leadership. Use AI tools and APIs to improve analytics workflows, self-service exploration, data-quality checks, and insight generation while validating accuracy, privacy, and business impact.

Owns digital SoC verification for advanced automotive communication semiconductors, collaborating with architects, designers, and software engineers from specification through coverage analysis and gate-level simulation. Responsibilities include developing reusable testbench architectures, automating tests and regressions, debugging simulation failures, validating networking and other semiconductor technologies, and supporting pre- and post-silicon verification infrastructure.

Build and maintain Warp’s analytics infrastructure, canonical data models, ETL and reverse-ETL pipelines, data quality systems, and self-service analytics tools. Define product and business metrics, analyze experiments, support pricing and revenue analytics, and conduct research into user behavior, growth, engagement, and churn. The role partners broadly across product, engineering, growth, revenue, and go-to-market teams while incorporating AI agents into data workflows.

Own quality evaluation for LLM-driven and agentic products by building regression suites, golden datasets, scoring rubrics, and test harnesses. Detect hallucinations, tool-calling failures, prompt regressions, and unsafe behavior. Define reliability metrics, integrate evaluations into CI/CD, improve observability and tracing, contribute to API and end-to-end automation, and coach QA engineers on AI testing practices.

Build and operate Helius’s bare-metal infrastructure platform. Responsibilities include automating server provisioning and lifecycle management, developing fleet tooling, standardizing CI/CD and deployment processes, implementing security controls, analyzing infrastructure costs, improving observability, participating in on-call response, and documenting operational procedures.

Design and implement Windows sensor detection and prevention features for the Falcon platform. Research attack techniques, develop user- and kernel-mode detection logic, own features from design through release, apply secure coding and CI/CD practices, troubleshoot customer issues, and collaborate across teams to improve telemetry and protections.

Lead the FinOps engineering team to design and implement backend services, cost-optimization tooling, data pipelines, APIs and dashboards, mentor engineers, and partner across engineering, finance, and product to drive cloud and vendor cost efficiency.

Own, build, and optimize Spark-based production data pipelines and ML data lake on GCP Dataproc to support recommender systems. Collaborate with ML engineers, resolve performance bottlenecks, and deliver scalable, reliable data products for AI-driven personalization.

The Senior Software Engineer will design and develop scalable systems for a cloud-based SaaS platform, lead technical discussions, and ensure high-quality code delivery.

The Senior Data Engineer will design and maintain streaming data pipelines, develop analytical databases, and ensure data system reliability while collaborating with teams across the organization.

Leads accounting systems transformation and finance automation, including NetSuite and Salesforce optimization, AI agent deployment, integrations, reporting, and internal tooling. Owns project plans, testing, training, go-live, controls, and executive reporting while partnering with engineering and cross-functional teams. Identifies automation opportunities, pilots AI vendors, supports SOX requirements, and trains finance staff on new workflows.

Leads and develops a team of IAM engineers, providing technical direction for backend architecture, distributed systems, engineering standards, and full project delivery. Partners with product, QA, SRE, and senior leadership to deliver customer-facing IAM platforms. Responsibilities include mentoring, hiring, onboarding, performance management, requirements clarification, execution oversight, and career development. Requires extensive engineering experience, Python knowledge, IAM expertise, distributed systems experience, Agile and SDLC understanding, and prior leadership experience.

Designs and executes automated Python tests for Nokia optical communication products, including system- and solution-level compatibility testing with third-party equipment. Creates test plans, analyzes defects, reports execution results, maintains scripts and documentation in Git, and collaborates with global software teams in an Agile environment.

Lead validation and interoperability testing for coherent optical module firmware. Develop Python-based automated tests, analyze reports and firmware defects, reproduce customer issues, support optical system integration testing in the Ottawa lab, and collaborate with firmware, hardware, and optical teams. Drive AI/ML-enabled testing improvements, configure optical test equipment, document procedures, and improve validation workflows for CMIS-compliant 400G/800G modules.

Owns end-to-end QA coverage across firmware, cloud services, and mobile applications for IoT products. Tests device-to-cloud communication, APIs, business logic, connectivity failures, offline operation, OTA updates, and rollback scenarios. Analyzes device and cloud logs, develops test data strategies, prioritizes automation scenarios, and maintains smoke and regression testing processes. Requires systems thinking, embedded and mobile testing experience, API testing, Agile QA processes, and familiarity with relevant test management tools.

Lead exploration and application of large language models and generative AI for enterprise contact-center automation. Translate research into high-performing, deployable ML systems; contribute across experimentation, implementation, and deployment; collaborate with engineering and product teams; optimize performance; and help shape team strategy, innovation, and professional growth.

Lead exploration and application of large language models and generative AI, translate research into deployable ML systems, and guide strategic direction. Develop solutions across experimentation, implementation, and deployment while collaborating with engineering and product teams to optimize performance and customer outcomes in contact center automation.

Build and scale data platforms, ETL pipelines, data lakes, warehouses, feature stores, and orchestration tooling. Integrate clickstream, relational, and unstructured data using Databricks and AWS. Partner with data scientists, ML engineers, product managers, and business stakeholders to support analytics, predictive modeling, and data-driven decisions. Maintain production systems, automate testing and monitoring, and communicate technical roadmaps and challenges.

Energy Analyst Interns support consulting teams by analyzing electricity and natural gas markets, building economic, financial, statistical, and power-system models, conducting regulatory research, preparing client deliverables, and supporting expert reports and presentations. The role requires quantitative analysis, literature review, clear communication, teamwork, and collaboration with senior consultants on financial, legal, and policy matters.

Design and develop machine-learning approaches for vehicle control, including learned vehicle dynamics models, adaptive controllers, data pipelines, evaluation metrics, and simulation tooling. Integrate learned models into safety-critical closed-loop systems and validate algorithms through offline experimentation, simulation, and on-vehicle testing. Collaborate with engineers and research scientists to combine classical control with AI for scalable self-driving technologies.

Investigate failures in complex medical devices across hardware, software, firmware, mechanical, MRI, and ultrasound subsystems. Reproduce failures, analyze logs and sensor data, perform root cause analysis, develop safe interim workarounds, and communicate findings. The role supports complaint handling, adverse-event evaluation, CAPA, risk-management updates, supplier investigations, and corrective-action verification while ensuring regulatory and patient-safety requirements are met.

Develops and supports ETL applications and data pipelines across legacy and modern platforms. Responsibilities include systems analysis, design, construction, testing, implementation, operational support, troubleshooting ETL processes and SQL workloads, performance tuning, and continuous improvement. The role requires expertise in ETL architecture, data warehousing, Unix scripting, Oracle or MySQL, application integration, and database development, with exposure to streaming technologies and modern languages such as Spark, Scala, Java, or Python.

Designs, develops, and supports scalable enterprise data warehouses, data lakes, cloud data platforms, and ETL/ELT pipelines. Responsibilities include SQL development, Snowflake and Databricks engineering, Spark and Python programming, data modeling, source-to-target mapping, testing, reconciliation, performance tuning, production support, and cloud modernization. The role translates business and technical requirements into reliable data solutions and collaborates with architects, analysts, application teams, and reporting stakeholders.