Senior Insurance Data Analytics Jobs in Ontario (NOW HIRING)

The Senior Data Analyst leads analytical framing, experimentation, business analysis, value realization, stakeholder engagement, and solution delivery support for AI-enabled business initiatives, helping teams turn complex or ambiguous opportunities into practical, measurable outcomes. 

Working closely with AI Enablement leads, Data Scientists, Data Engineers, business stakeholders, and technology teams, this role translates business opportunities into measurable AI use cases and guides the evaluation, implementation, and adoption of AI solutions through evidence-based analysis and recommendations. 

The successful candidate combines strong analytical skills with business acumen, acts as a trusted analytics partner, and bridges technical and business stakeholders to help AI initiatives deliver practical, measurable value while supporting consistent and repeatable delivery practices. 

 What you will do: 

• Lead the translation of complex or ambiguous business opportunities into clear AI use cases, analytical questions, success measures, and measurable outcomes that can be tested and evaluated. 

• Own practical analytical approaches, including experiments, pilots, measurement frameworks, reporting, and interpretation, to assess whether AI-enabled solutions are delivering value. 

• Build confidence in AI solutions by guiding data collection, validation, testing, quality assurance, and performance monitoring activities. 

• Partner with Data Engineers and Data Scientists to identify source-system data, manage it through the data lifecycle, and develop analytical products that support AI-enabled solutions. 

• Turn analytical findings, business context, and evaluation results into clear recommendations that influence stakeholder decisions about AI opportunities, adoption, prioritization, and next steps. 

• Support adoption and repeatable delivery by developing workshops, training, job-aides, measurement practices, and other materials that help teams understand and apply AI solutions effectively. 

What you will bring:

Required 

• Degree in Statistics, Mathematics, Analytics, Data Science, Economics, Business, Engineering, or an equivalent combination of education and experience. 

• 5+ years of experience applying data, analytics, business analysis, or digital enablement practices to solve business problems and improve outcomes. 

• Experience translating business needs into analytical questions, success measures, requirements, and practical recommendations. 

• Experience designing or supporting experiments, pilots, performance measurement approaches, or value realization assessments. 

• Experience working with business stakeholders and technical partners to define requirements, interpret findings, and support implementation decisions. 

• Proficiency with analytics and reporting tools such as Power BI, SQL, or comparable platforms. 

• Working knowledge of data platforms, programming, or cloud-based analytics environments such as Azure, Databricks, Python, or comparable tools. 

• Experience working in Agile or iterative delivery environments. 

• Demonstrated ability to lead through influence, collaboration, and subject-matter credibility rather than formal authority. 

• Experience providing guidance, peer support, or informal coaching to analysts or multidisciplinary partners. 

• Strong stakeholder engagement, facilitation, and communication skills. 

• Ability to bridge technical and business audiences effectively.

• Reliability Status Security Clearance - this can only be completed with candidates who receive an offer of employment. This is a personal security status that is required as a condition of employment before an employee can gain access to Protected B information, assets or work sites as outlined by the Government of Canada website. The cost of submitting these checks will be covered by Canada Life. 

Preferred 

• Experience supporting AI, machine learning, generative AI, automation, or advanced analytics initiatives. 

• Exposure to AI governance, responsible AI, privacy, or data governance practices. 

• Experience supporting proof-of-concepts, pilots, or adoption activities for emerging technology solutions. 

• Strong foundation in research methods, measurement design, evaluation methodologies, or benefits realization.