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Insurance Data Analytics Jobs in Ottawa, ON (NOW HIRING)

Perform data analysis, visualization, and modelling with large datasets; * Independently ... Comprehensive Health and Dental insurance package; * Competitive vacation and paid time off;

More specifically, you will work with business analysts and operational stakeholders to identify ... insurance, Employee Assistance Plan and Well-Being program. Retirement Savings Plans (RRSP, DCPP ...

New

Experience with pension plan and group insurance Soft skills * Capable of communicating in ... Detailed oriented, analytical and problem-solving aptitude * Proactive, strong-minded, quick ...

Senior Solution Analyst

Ottawa, ON ยท Hybrid

CA$90K - CA$120K/yr

... external market salary data, internal pay equity and the knowledge, skills, experience and ... About The Wawanesa Mutual Insurance Company Founded in 1896, The Wawanesa Mutual Insurance Company ...

Finance Analyst - McNally

Hamilton, ON ยท On-site

CA$75K - CA$90K/yr

This role evaluates construction job cost data, and completes analysis and reporting for management ... Reviews and understands prime contract and change orders, including insurance, taxes, payment terms ...

Finance Analyst

Ottawa, ON ยท On-site

CA$85K - CA$105K/yr

Effectively use the right data, reports, and tools for risk analysis and benchmarking. Assist with ... insurance, disability, retirement plans with matching, and generous paid time off. We believe in ...

Catastrophe Risk Specialist

Ottawa, ON ยท Hybrid

CA$85K - CA$115K/yr

Analyze historical data, scientific research, and insurance claims to enhance model accuracy. * Collaborate with actuaries, underwriters, and analysts to understand risk exposures, and manage ...

Comprehensive Health and Dental insurance package; * Competitive vacation and paid time off ... Data Fusion and Analytics, Data Science, and Research and Engineering. Larus software products ...

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Insurance Data Analytics information

What are the key skills and qualifications needed to thrive in insurance data analytics?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

What are the typical responsibilities of someone working in insurance data analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making processes within insurance companies. They use tools like Excel, SQL, and data visualization software to interpret claims, policy data, and customer information, helping improve underwriting, pricing, and fraud detection.

Is data analytics a high paying job?

Data analytics roles, including those in insurance data analytics, are generally considered well-paying compared to many other entry-level positions. Salaries vary based on experience, skills, and location, but professionals with expertise in tools like SQL, Python, or R often earn competitive wages and have strong job growth prospects.

How much does an insurance data analyst make?

The average salary for an insurance data analyst typically ranges from $60,000 to $90,000 annually, depending on experience, location, and industry. Professionals with advanced skills in data visualization, statistical analysis, and tools like SQL or Python may earn higher salaries, especially in larger organizations or metropolitan areas.

What is insurance data analytics?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the most commonly searched types of Insurance Data Analytics jobs in Ottawa, ON? The most popular types of Insurance Data Analytics jobs in Ottawa, ON are:
What cities near Ottawa, ON are hiring for Insurance Data Analytics jobs? Cities near Ottawa, ON with the most Insurance Data Analytics job openings:
Infographic showing various Insurance Data Analytics job openings in Ottawa, ON as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 25% Part Time, 1% Temporary, and 5% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Data Analytics Engineer - Corporate Data Analytics Group

Canadian Bank Note Company

Nepean, ON โ€ข On-site, Remote

Full-time

Medical, Life, Retirement

Re-posted 14 days ago


Job description

Company Description

Canadian Bank Note Company (CBN) is a leader and trusted provider of secure document and adjacent enterprise-level system solutions across the following domains: border security, civil identity, driver licence/identification and vehicle information, excise control, currency, lotteries and charitable gaming.

Our Corporate Philosophy and 7 Core Principles shape and guide our corporate behaviours and underpin the sense of community you will experience at CBN. We seek long-term relationships with our employees and offer a competitive compensation package that includes health, medical and life insurance benefits and a defined contribution pension plan with company matching.

Job Description

Internal Job Title: Data Analytics Engineer

Job Type: Permanent, Full-time

Location: Ottawa, Ontario

Work Model: Remote

Job Status: Existing Vacancy

Position Summary

The Data Analytics Engineer plays a critical role in preparing enterprise data to be AI-ready by designing rich semantic layers and business context that enable advanced analytics, self-service BI, and AI-powered decision-making. This role focuses on transforming curated data into trusted, governed, and reusable data products that can be safely consumed by business users, copilots, and machine learning models across the organization.

Key Responsibilities

Business Partnership & Domain Alignment

  • Partner with business stakeholders to translate domain knowledge into structured analytical and semantic representations.

Semantic Modeling & Data Foundation

  • Design, develop, and maintain enterprise semantic models that represent business meaning, metrics, and relationships across data domains.
  • Collaborate with data engineers to shape silver and gold datasets that support semantic clarity and downstream AI consumption.
  • Build AI-ready data products by enriching datasets with business definitions, hierarchies, metadata, and contextual logic.

BI Development & Metric Standardization

  • Develop and optimize Power BI semantic models, datasets, and metric layers to support BI, Copilot, and AI use cases.
  • Create and manage standardized KPIs and calculations using DAX, ensuring consistency and reuse across analytics and AI workloads.
  • Document business logic, data definitions, and metric context to support discoverability and AI-assisted querying.

Governance, Security & Trusted Data

  • Implement data governance controls including row-level security (RLS), object-level security, sensitivity labels, and certified datasets.

Data Product Enablement & AI Integration

  • Publish trusted semantic models and datasets to enable self-service and AI-assisted analytics at scale.
  • Support integration of analytics models with AI and ML workflows, including retrieval-augmented generation (RAG) scenarios.

Performance Optimization & Reliability

  • Monitor and optimize model performance, refresh reliability, and query efficiency.

Standards & Continuous Improvement

  • Contribute to analytics and AI standards and best practices through the Data & AI Community of Practice.
Qualifications

Mandatory Requirements

  • Legally eligible to work in Canada.
  • Fluent in English (speak, read, write).
  • Able to obtain (in a timely manner) and maintain Government of Canada Secret (Level II) security clearance.

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
  • Understanding of the following:
    • Semantic modeling concepts including metrics, hierarchies, and dimensional modeling.
    • Data governance principles and secure data access patterns.
  • 8+ years of relevant professional experience, including:
    • 3+ years of professional experience in analytics, business intelligence, or data modeling roles.
    • 3+ years of hands-on experience with Power BI semantic modeling, DAX, and dataset design.
    • 3+ years of experience working with SQL-based analytical datasets.
    • Ability to translate business concepts into structured analytical and semantic representations.

Preferred Qualifications

  • Microsoft Certifications:
    • Power BI Data Analyst Associate (PL-300) or Fabric Analytics Engineer Associate (DP-600).
  • Knowledge of data catalogs, business glossaries, and metadata management.
  • Experience with the following:
    • Microsoft Fabric semantic models, OneLake, and data products.
    • Preparing datasets for AI/ML or Copilot scenarios (e.g., feature tables, RAG inputs).
    • Manufacturing, software, or regulated environments.

Additional Information

Equal Opportunity Statement

Our organization is committed to employment equity and diversity in the workplace. We actively encourage applications from women, Indigenous Peoples, persons with disabilities, members of visible minorities, and LGBTQ2+ individuals.

We are dedicated to removing barriers and fostering an inclusive workplace that reflects society and we are committed to providing an accessible and inclusive recruitment process in accordance with the Accessibility for Ontarians with Disabilities Act (AODA).

If you require accommodation at any stage of the hiring process, please contact us at recruitment@cbnco.com so that appropriate arrangements can be made.

AI Use in Recruitment Statement

As part of our commitment to transparency and fairness in hiring, we disclose that artificial intelligence (AI) tools may be used at certain stages of our recruitment process. These tools assist in tasks such as resume screening, candidate matching, and interview scheduling. All AI-assisted decisions are subject to human oversight to ensure fairness, accuracy, and compliance with applicable laws.

We are committed to the responsible, transparent, and accountable use of AI, in alignment with Ontario’s Responsible Use of Artificial Intelligence Directive and the requirements under the Working for Workers Four Act. This includes taking steps to mitigate bias, protect candidate privacy, and ensure that AI does not unfairly influence hiring outcomes.

If you have questions or concerns about how AI is used in our hiring process, please contact us at recruitment@cbnco.com .