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Insurance Data Analytics Jobs in British Columbia

Manager, Data Analytics

Burnaby, BC ยท On-site

CA$120K - CA$150K/yr

The Data Analytics Manager, Fraud will be part of Remitly's Identity & Trust Analytics Team ... Life Insurance & Disability * Continuing education and travel benefits Our Connected Work Culture:

This role will collaborate with the finance, actuarial and audit teams to support data analysis ... About us: At ICBC, it's our job to make sure the car insurance system works for all British ...

Posted today

... to mining, insurance, and government intelligence. Our mission is to build the world's most ... Space, aerospace, satellite, geospatial, earth observation, data/analytics, or complex technology ...

Data Scientist II

Burnaby, BC ยท On-site

CA$128K - CA$144K/yr

Experience designing, running, and analyzing experiments to inform business strategy * A degree in ... Life Insurance & Disability * Continuing education and travel benefits Our Connected Work Culture:

Data Coordinator

Mill Bay, BC ยท Hybrid

CA$66K - CA$100K/yr

Generate reports and provide data analysis to support decision-making processes. * Ensure ... insurance, Employee Assistance Plan and Well-Being program. Retirement Savings Plans (RRSP, DCPP ...

Analyze and extract data from 3D models provided by designers or modelers. \n * Process, organize ... Comprehensive group insurance program. \n * RRSP group program with an employer contribution to a ...

CA$125K - CA$175K/yr

Analyze and extract data from 3D models provided by designers or modelers. \n * Process, organize ... Comprehensive group insurance program. \n * RRSP group program with an employer contribution to a ...

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Insurance Data Analytics information

See British Columbia salary details

$21K

$82.2K

$169.5K

How much do insurance data analytics jobs pay per year?

As of Jul 29, 2026, the average yearly pay for insurance data analytics in British Columbia is $82,200.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,500.00 and $117,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Insurance Data Analytics position, and why are they important?

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 collects, processes, and analyzes insurance data to identify trends, assess risks, and support decision-making. They use tools like Excel, SQL, and data visualization software to create reports and models that improve underwriting, claims management, and pricing strategies.

How much does an insurance analyst make?

The average salary for an insurance analyst is around $65,000 to $85,000 per year, depending on experience, location, and industry. Entry-level roles typically start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Strong analytical skills and proficiency with data tools like Excel or SQL are often required.

Will AI replace a data analyst?

AI can automate routine data processing and analysis tasks, but the role of a data analyst, including those in insurance data analytics, involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Therefore, AI is more likely to augment rather than fully replace data analysts, who also need skills in data visualization, domain knowledge, and communication. Continuous learning and proficiency with analytics tools remain important for the role.

What is an Insurance Data Analytics job?

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 popular job titles related to Insurance Data Analytics jobs in British Columbia? For Insurance Data Analytics jobs in British Columbia, the most frequently searched job titles are:
What job categories do people searching Insurance Data Analytics jobs in British Columbia look for? The top searched job categories for Insurance Data Analytics jobs in British Columbia are:
Infographic showing various Insurance Data Analytics job openings in British Columbia as of July 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 81% Physical, 6% Hybrid, and 13% Remote job distribution, with an average salary of $82,200 per year, or $39.5 per hour.

Manager, Data Analytics

Remitly

Burnaby, BC โ€ข On-site

CA$120K - CA$150K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 5 days ago


Job description

Job Description:

At Remitly, we believe everyone deserves the freedom to access, move, and manage their money wherever life takes them. Since 2011, we've tirelessly delivered on our promise to customers sending money globally, providing secure, simple, and reliable ways to manage their money, ensuring true peace of mind. Whether it's supporting loved ones back home, growing a business across continents, or pursuing new opportunities abroad, we're not just here to move money- we're here to move our global customers forward.
We're looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation. If that's you and you're ready to do the most meaningful work of your career-we invite you to join over 2,800 passionate Remitlians worldwide who are united by our vision to transform lives with trusted financial services that transcend borders.

About the Role:

The Data Analytics Manager, Fraud will be part of Remitly's Identity & Trust Analytics Team, reporting to the Senior Manager, Fraud Program and Analytics. You will lead and develop a team of analysts while remaining hands-on in the data yourself. You will apply data science and analytics techniques to drive rapid, rational decision-making across Remitly's Transaction Integrity program - spanning Fraud, Scams, and Promo Abuse. You will develop deep expertise in our fraud systems, translate complex data into clear insights, and leverage AI to accelerate analytical work - partnering closely with program managers, product managers, engineers, and operations to protect customers and enable sustainable growth.

You Will:

  • Lead and develop a team of analysts - providing mentorship, technical guidance, thoughtful feedback, and career development support to help your team grow and do their best work.
  • Become an expert on Remitly's Payments Fraud (Scams, Chargebacks, Promo Abuse) data, customer experience, and policy.
  • Build a unified understanding of how our data, customer experiences, and Transaction Integrity goals align across products and geographies.
  • Own and evolve the metrics used to evaluate fraud system performance, operational effectiveness, and customer friction.
  • Formulate hypotheses, design and evaluate product experiments, and translate analytical findings into clear, actionable recommendations for cross-functional stakeholders.
  • Partner with program and product managers to generate insights and help define and execute longer-term fraud prevention strategies and roadmaps.
  • Serve as a technical resource for your team, such as supporting SQL-heavy analyses, data quality investigations, or complex modeling when needed.
  • Leverage AI tools and agentic workflows to accelerate your team's analytical output - actively exploring how emerging AI capabilities can improve the speed, quality, and scale of fraud analytics.
  • Prioritize and manage the team's analytical roadmap, balancing reactive requests with longer-term strategic work.

You Have:

  • 5+ years of experience in a data analyst role or similar full-time professional experience, with at least 2-3 years of people management experience.
  • Experience in fraud, risk, trust & safety, fintech, or adversarial analytics strongly preferred.
  • Bachelor's degree in mathematics, engineering, economics, or another quantitative field (or equivalent additional experience).
  • Strong SQL proficiency; working knowledge of Python or R for data analysis.
  • Expertise with statistical concepts (e.g., A/B testing, probability theory, forecasting) and how they apply in real-world fraud or risk contexts.
  • Experience distilling business problems from stakeholder discussions, developing hypotheses, building an analytical framework, carrying out analyses, and writing clear recommendations.
  • Strong data storytelling skills, including data visualization, technical writing, and the ability to communicate complex findings to non-technical audiences.
  • Proven ability to coach and develop analysts, elevate team output through technical guidance, and navigate ambiguous problem spaces.
  • Demonstrated experience using AI tools (e.g., LLM-assisted analysis, agentic workflows, or AI-powered tooling) to enhance analytical productivity and quality.

Compensation Details. The starting base salary range for this position is $120,000 - $150,000. In Canada, Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role.

Our Benefits

  • Four weeks vacation
  • Health Benefits
  • Mental Health & Family Forming Benefits
  • RRSP plan with company match
  • Employee Stock Purchase Plan (ESPP)
  • Life Insurance & Disability
  • Continuing education and travel benefits

Our Connected Work Culture: Driving Innovation, Together

At Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster. For corporate team members, we have an in-office expectation of at least 50% of the time monthly, typically achieved by coming in three days a week. This creates a consistent, meaningful overlap that supports team norms and business needs. Managers also have the flexibility to set higher expectations based on their team's specific needs. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.

Remitly is an E-Verify Employer

At Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.

Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.