Top Data Analytics Jobs in Toronto

Lead product operations analytics to convert raw product and business data into actionable insights. Build dashboards and decks, define KPIs, partner with Data & Analytics to establish metrics frameworks, translate business questions into data requirements, enable cross-functional teams, present roadmap recommendations, and leverage AI/LLMs to automate workflows and reporting to drive revenue, retention, and growth.

Own and scale Wrapbook’s analytics layer, including ETL/ELT pipelines, data models, governed metrics, semantic layers, canonical datasets, and self-service analytics tools. Partner with Engineering and business stakeholders to define analytical solutions, ensure data quality, optimize warehouse performance, and maintain production reliability through testing, monitoring, alerting, and incident resolution. Establish analytics engineering standards, mentor team members, document data for human and AI consumers, and evaluate new tools.

Embed with client engineering teams to deploy, integrate, and scale enterprise generative AI solutions. Build agentic systems, train and serve LLMs with Vertex AI, integrate models with BigQuery/AlloyDB/Spanner, implement streaming inference pipelines, and ensure operational reliability while collaborating with stakeholders to translate business goals into production-grade architectures.

Lead supply chain data and systems strategy for data center projects: develop analytics and BI datasets, build KPI dashboards, manage supply chain systems (ERP/SLM/Oracle/Power BI), enforce master data management, and support cross-functional teams to enable data-driven decision-making and automation.

Build and scale the finance function: own core accounting, reporting, close processes, internal controls, compliance, and finance systems. Improve AP/AR, treasury, tax, audit readiness, automation, forecasting, and stakeholder reporting while partnering with the CFO and leadership.

Lead credit policy and underwriting initiatives using Stripe's data and third-party sources. Architect credit policies, analyze portfolio trends, integrate bureau and alternative data, provide risk recommendations, collaborate with product, data science, engineering, and capital markets, and scale risk processes and outsourced workflows.

Lead marketing measurement and analytics across campaign, channel, and funnel; own attribution and forecasting; apply ML/LLM techniques for propensity scoring, forecasting, anomaly detection, and automated insights; manage marketing data stack (Salesforce, MAP, warehouse); build dashboards, deliver executive analyses, and mentor analysts.

Lead liquidity risk analytics and implementations: develop quantitative risk models, implement vendor liquidity solutions (Algorithmics/SunGard), design data extracts and database structures, perform stress testing and regulatory compliance (Basel/FSA/OSFI), test reports, and liaise with treasury, finance and risk senior stakeholders.

As an Engagement Manager, lead BI projects, guide teams to transform data into actionable insights, and develop BI strategies ensuring data integrity and quality.

Lead enterprise-wide business process transformation and EUC governance in a regulated banking environment. Assess current-state processes, design future-state operating models, modernize analytics (Power BI) and automation (Power Platform, ServiceNow), drive remediation of spreadsheet/Access-driven EUCs, define KPIs and controls, ensure audit and regulatory alignment, and lead cross-functional stakeholders to deliver measurable operational improvements.

Support Financial Planner business analytics: set targets, produce performance and compensation analysis, design scorecards, build dashboards and recurring reports, integrate and validate data, automate reporting, and deliver executive-ready insights and ad-hoc deep dives to inform performance management and strategic decisions.

Lead growth and player behavior analytics across sportsbook, casino, and poker products. Partner with Revenue Ops, Marketing, Product, and VIP to run retention, bonus optimization, segmentation, funnel/cohort analyses, and A/B tests. Build predictive models and apply ML/AI tooling to generate actionable insights and recommendations that drive engagement, personalization, and ROI.

Designs and delivers data analytics and BI solutions across the analytics lifecycle, produces actionable insights, solves complex problems independently, mentors junior staff, and contributes to policies and technical solutions for large-scope projects.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

The Associate Director leads strategic planning, forecasting, and analytics for Ipsen Canada, driving insights for business decisions and overseeing projects critical to commercial success.

The Senior Product Manager will lead product strategy and execution, collaborating with cross-functional teams to enhance life sciences analytics products and meet customer needs.

The Data Product Manager will lead the development of enterprise data products by translating business needs into scalable data solutions, managing analytics projects, and coordinating with global teams to ensure efficient delivery and optimization of data initiatives.

Support stakeholders by profiling, mapping, and validating financial reconciliation datasets. Build complex SQL queries and Python workflows, and use Snowflake and Databricks to design, transform, and manage large-scale finance data for reporting, reconciliation, and analytics. Ensure data quality, perform root-cause analysis, and support governance and documentation.

Own and extend the company data platform: model business logic in dbt on BigQuery, maintain pipelines and Airflow orchestration, ensure data quality and cost control, serve metrics via Hasura/Metabase, and deliver documented, tested marts and KPIs for leadership, marketing, and operations.

Lead a business analytics team to deliver data-driven insights, KPIs, dashboards and AI-enabled solutions. Partner with stakeholders to define strategy, automate reporting, prototype AI use cases, and build scalable analytics products while ensuring data quality and governance.

Lead enterprise people analytics strategy and people technology, build a small high-performing team, deliver predictive and prescriptive workforce insights, ensure data governance/security, integrate people data with finance and performance, and partner with senior leaders and Technology to embed data-driven decision-making across the organization.

The Account Executive at CoStar is responsible for selling new business, managing client portfolios, and driving growth through the entire sales process in the commercial real estate sector.

Lead front-end analysis for data and analytics initiatives: define solution intent, assess feasibility and data quality, perform SQL profiling and source-to-target mapping, document data definitions and business rules, identify risks, and support delivery, adoption, and reporting across business and technical stakeholders.

The Associate Consultant will provide analytical support for client projects in life sciences, assist in developing proposals, conduct quantitative analyses, and communicate findings to stakeholders, while working collaboratively in a team environment.

Provide high-quality analytical support to life sciences client projects: perform quantitative and qualitative analyses, develop client deliverables (Excel/Power BI/PowerPoint), own defined workstreams, support client interactions, and contribute to internal knowledge and tool development. Work with imperfect data, document assumptions, and collaborate with senior consultants to deliver timely recommendations.