Top Python Jobs in Toronto

Partners with business functions to advise on and build AI-powered solutions using Microsoft Copilot Studio, Claude, and low-code platforms. Translates requirements into solution designs, manages testing and deployment, develops reusable prompts and agents, evaluates proofs of concept, and supports AI adoption. Ensures solutions meet security, privacy, regulatory, and responsible AI requirements while collaborating with enterprise AI and learning teams.

Architect, develop, and maintain scalable Selenium-based automation frameworks for web UIs, APIs, microservices, and databases. Build reusable test libraries, implement BDD and TDD, integrate AI-driven testing utilities, analyze failures, and support parallelized CI/CD pipelines. Collaborate with engineering and product teams on shift-left testing, testability, acceptance criteria, and defect resolution in an Agile Scrum environment.

Analyze full-funnel B2B marketing performance using dashboards, SQL, attribution modeling, and CRM data. Build Tableau or Looker Studio reporting, query Redshift data, and apply Python, AI APIs, prompt engineering, and automation to streamline data processing and performance summaries. Partner with campaign, web, and sales operations teams to improve tagging, KPI consistency, lead velocity, and conversion insights.

Develop end-to-end cloud-native applications across frontend, backend, APIs, AI, and data layers. Build React interfaces, Python and Java services, LLM and agentic AI solutions, RAG systems, data pipelines, and Azure-based infrastructure. Responsibilities include testing, deployment automation, security, observability, troubleshooting, architecture, and cross-functional collaboration.

Performs data engineering across modeling, profiling, quality, ingestion, ETL, metadata, lineage, and governance. Develops complex data models, ETL frameworks, and enterprise data solutions; supports testing, deployment, release management, architecture reviews, and issue resolution. Partners with technical and business stakeholders, ensures compliance with data and security standards, leads engineering initiatives, mentors team members, and communicates complex technical details to nontechnical audiences.

Leads strategic Treasury data initiatives across banking and financial services. Partners with stakeholders to define data requirements, build trusted data products, perform modeling and analysis, and ensure data quality, lineage, governance, and regulatory readiness. Acts as a product owner, manages delivery and testing, investigates data issues, and drives stakeholder adoption through change management, training, and communication.

Conduct computational oncology research using AI/ML, bioinformatics, and multimodal biomedical data. Develop foundation models, biomarker discovery methods, therapeutic response models, privacy-preserving workflows, federated analyses, and scalable genomic pipelines. Collaborate with computational biologists, clinicians, software developers, wet-lab scientists, and industry partners. Contribute to data governance, ethics, regulatory documentation, publications, and translational cancer research.

Supports development and maintenance of backend services, satellite network infrastructure, and mission control automation. Collaborates with satellite operators and product managers to deliver reliable ground systems, writes tests and documentation, and participates in software and code reviews. The intern works hands-on across Kepler’s software stack and must complete a full-time internship beginning January 2027 while returning to post-secondary studies afterward.

Develop predictive weather, spatio-temporal, and time-series models using meteorological and client sales data. Analyze complex datasets, optimize machine learning performance with distributed frameworks, and manage models through deployment and monitoring. Collaborate with sales, marketing, product, engineering, and revenue teams to deliver scalable B2B data products, APIs, and actionable commercial insights. Document model architectures, data lineage, and decision logic.

Build and operate CI/CD, testing, release, and GPU-enabled infrastructure for NVIDIA Isaac Sim. Responsibilities include managing cloud and on-premises runners, integrating automated simulation and performance tests, optimizing build pipelines, creating reproducible environments and artifacts, monitoring infrastructure health, troubleshooting complex software and GPU issues, and strengthening release security and traceability.

Lead software engineer responsible for designing and developing robust, automated technology solutions for margin and collateral platforms. The role involves building RESTful APIs, event-driven microservices, and user interfaces; collaborating with product teams and users; applying TDD and clean-code practices; and solving complex engineering problems in a global financial technology environment. Cloud, distributed systems, and financial services experience are beneficial.

Designs, deploys, maintains, and supports infrastructure and middleware for FX electronic trading applications. Provides technical leadership across messaging middleware, operating systems, networking, hardware, performance engineering, and web middleware. Coordinates replatforming and migration initiatives, translates application needs into infrastructure designs, supports production issues, contributes to releases and DevOps efforts, and leads engineers while collaborating with global technology and business teams.

Build and lead Northland’s gas commercial capability by securing and optimizing gas supply, transportation, and storage. Originate and negotiate commodity and asset management agreements, structure procurement and hedging strategies, optimize gas assets, support gas-fired project development, manage market and counterparty risks, and coordinate with operations, development, finance, risk, legal, marketers, and pipelines. The role also establishes gas governance processes, provides forecasting and budget inputs, and serves as the internal gas markets subject-matter expert.

Supports commercial optimization of generation and energy-storage portfolios across electricity markets. Analyzes market prices, congestion, dispatch, settlements, and asset performance; develops optimization models, data pipelines, dashboards, and analytical tools using Python and SQL; evaluates revenue-stacking opportunities; monitors third-party optimizers; investigates value leakage; and presents actionable recommendations to commercial and operational stakeholders.

Build and operate secure, scalable Azure and Google Cloud AI/ML platforms. Own Terraform-based infrastructure, GitHub Actions pipelines, Python tooling, cloud networking, identity, secrets, compliance, observability, and production operations. Develop self-service platform abstractions and generative AI consumption patterns, including private endpoints, RAG, model gateways, MLOps/LLMOps, and evaluation tooling. Lead architecture discussions, code reviews, engineering standards, vendor evaluations, and mentorship while partnering with security, network, risk, and architecture teams.

Lead commercial decision science projects for a rare disease business, developing predictive and machine learning models using healthcare and real-world data. Apply statistical modeling, experimental design, causal inference, survival analysis, forecasting, and AI-assisted analytics. Translate findings into commercial recommendations while ensuring privacy, explainability, fairness, validation, monitoring, and governance. Partner with cross-functional teams, manage project milestones, communicate insights to technical and non-technical stakeholders, and coach peers.

Analyzes hitting biomechanics, performance, scouting, and health data to identify player-development opportunities. Builds models, reports, visualizations, and analytical frameworks; conducts applied research; and translates movement insights into practical recommendations for coaches, players, and decision-makers. Collaborates across performance science, baseball research, scouting, and player development to support evaluations, intervention planning, progress monitoring, and development strategies.

Provides business systems analysis and technical leadership for asset management technology. Gathers and documents complex requirements, leads solution design discussions, prepares design and quality assurance documentation, and supports end-to-end project implementation. Advises stakeholders and project teams, resolves ambiguous challenges, analyzes data, performs gap analysis, and mentors technology professionals. The role primarily supports Rates and cross-asset risk management platforms using data warehousing, Databricks, SQL, Power BI, and related tools.

Design, develop, and implement AI-enabled solutions to automate and accelerate the software delivery lifecycle. Build AI agents and workflows using tools like Claude Code and Copilot, improve developer productivity, support production applications, troubleshoot incidents, and evolve SDLC into AI-driven ADLC while collaborating with stakeholders across delivery teams.

Develop machine learning and advanced analytics models for algorithmic trading across multiple asset classes. Build predictive models and production ML pipelines, analyze large datasets, research techniques such as generative AI and deep learning, and collaborate with trading, investment banking, and corporate banking stakeholders. Communicate insights to business leaders and visualize findings to support strategic decisions and improve trading performance.

Develop machine learning and advanced analytics models for algorithmic trading across multiple asset classes. Build predictive models and reproducible production pipelines, analyze large datasets, research techniques such as generative AI and deep learning, and communicate insights to trading, banking, and senior management stakeholders.

The Vice President, Data Scientist will develop and implement machine learning models to enhance algorithmic trading strategies and provide data-driven insights for Investment Banking and Corporate Banking.

Own the end-to-end data architecture for Genesys, Verint, and related sources. Design Medallion and Kimball architectures, ingestion strategies, dimensional models, orchestration, data-quality controls, reconciliation, and failure recovery. Build and optimize Databricks, Delta Lake, Snowflake, API, and vendor-feed pipelines using T-SQL, Spark SQL, and Python/PySpark. Lead parallel-run validation, legacy decommissioning, and communicate architectural decisions to technical and business stakeholders.

Develops, configures, tests, deploys, and supports Genesys Cloud CX solutions across voice, digital, IVR, chatbot, workforce management, knowledge management, APIs, and enterprise integrations. Translates business requirements into technical specifications, builds integrations using Python and REST APIs, manages releases across environments, troubleshoots production issues, performs root-cause analysis, and maintains documentation. Provides operational support, participates in on-call coverage, and ensures security, performance, and change-management standards are met.

Process mandatory and voluntary corporate actions while designing automation workflows using n8n, AI, Python or JavaScript, SQL, APIs, and database integrations. Extract data from corporate action notices, reconcile and post client payments, monitor events, audit manual processes, implement validation controls, and collaborate with Operations and Engineering. Requires brokerage or wealth management back-office experience and knowledge of corporate actions, depositories, and Canadian and US regulatory requirements.