Top Data Jobs in Toronto

The role involves building and optimizing big data pipelines, designing data architectures, collaborating with data scientists, and driving technical strategy for data processing infrastructure.

The Senior Network Engineer will manage and optimize in-house and cloud-based networks, ensuring security and availability while troubleshooting complex network issues.

Senior Data Scientist supporting Canadian business units to design, develop, and deploy ML and GenAI solutions (including agents, chatbots, RAG, and vector-based retrieval). Translate business goals into analytics, perform feature engineering, model training/evaluation, prompt engineering, and mentor junior staff. Provide technical leadership, design artifacts, stakeholder communication, and drive continuous improvement.

Design, develop, and maintain scalable data pipelines on Azure Databricks. Translate business requirements into code, perform impact analysis, participate in code reviews, support production and UAT, and troubleshoot complex application issues to improve client-facing data solutions.

Use legal expertise to create and evaluate training data for AI models. Perform legal research and analysis, provide actionable feedback, follow annotation best practices, support senior staff, present findings to stakeholders, and advocate for responsible AI.

Lead governance, maintenance, and enhancement of Anaplan and finance data processes. Ensure month/quarter close data integrity, support budgeting/forecast cycles, deliver reporting and ad hoc financial analysis, drive process improvement and automation, and manage a team of reporting/data resources while partnering across Finance, Technology, Data, and Risk stakeholders.

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 analytics for Internal Audit Claims: extract, transform, reconcile, and validate large claims datasets; build and maintain Power BI reports/dashboards; perform QA and tie-outs; support automation, bots/AI enablement, and executive reporting; mentor other analysts and partner with audit, IT, and business stakeholders to deliver repeatable, validated analytics.

Manage relationships with strategic healthcare clients, oversee complex projects, innovate operational processes, and lead large teams to improve AI training and application.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Develop and extend data ingestion pipelines for AI model training, manage cloud infrastructure, and collaborate with AI scientists. Bring new audio data sources into the system.

Analyze player behavior, game health, engagement, retention, monetization, and live-service performance for Marvel Strike Force. Own KPI reporting, explain trends and variances, evaluate experiments, validate analytics tracking, and deliver actionable insights to product, design, marketing, live operations, and leadership teams. Use SQL, Python, reporting tools, and AI-enabled workflows while maintaining data quality, privacy, and analytical rigor.

Analyze, extract, clean, and model large datasets from multiple systems; build data warehouses and predictive models; create financial analyses, dashboards, and client reporting; implement and monitor models with client teams; support client relationships and contribute to proposals and marketing as needed.

Perform end-to-end BI and data analytics work: extract and transform large datasets, build data warehouses and predictive models, create dashboards and reporting, manage client relationships, oversee analysts, and contribute to proposals and marketing as needed.

Design, train, and deploy spatio-temporal and time-series ML models integrating weather and client data. Perform exploratory analysis, optimize model performance using distributed frameworks, own model lifecycle (testing, deployment, monitoring), document technical work, and collaborate cross-functionally to deliver scalable B2B data products and commercial insights.

Drive data analytics for a warehouse design platform: clean and analyze large, messy supply chain datasets, identify repeatable patterns, build prototypes and visualizations, and translate insights into product features to automate manual spreadsheet work.

Lead and deliver complex analytics, machine learning, and generative AI initiatives from problem framing to implementation. Design model strategies, evaluate AI/LLM solutions and agentic workflows, translate results into business recommendations, prepare business cases, mentor junior data scientists, champion Responsible AI and governance, and collaborate with product, engineering, and business partners to drive scaled AI outcomes.

Own the end-to-end data science function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence leadership decisions. The role requires independently structuring ambiguous problems, using SQL or Python, communicating findings clearly, and driving measurable business outcomes.

Own the end-to-end analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to influence decisions and drive measurable outcomes. The role requires strong analytical ability, independent problem-solving, clear communication, and ownership of ambiguous initiatives.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to communicate findings, influence decisions, and drive measurable outcomes. The role requires strong analytical problem-solving, independent execution, and persuasive communication.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, pull and structure data, build reports, run analyses, design experiments, communicate insights, and drive recommendations and decisions with cross-functional stakeholders. Requires strong analytical thinking, independent execution, persuasive communication, and experience solving ambiguous problems in consulting, investment banking, or high-growth technology.

Own end-to-end data science for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires independent analytical execution, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives that drive measurable business outcomes.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate insights; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent data work, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives from end to end.