Data Specialist, Corporate Actuarial

Economical is part of Definity, which includes some of Canada’s most long-standing and innovative insurance brands, including Economical Insurance, Sonnet Insurance, Family Insurance Solutions, and Petline Insurance. With strong roots that date back to 1871, Definity has grown to become a digital leader in the insurance industry. We’re proud to help our clients and communities adapt and thrive in a world of constant change.

Our promise to you: It’s better here. Why? Because we CARE, and we provide an employee experience that’s collaborative, ambitious, rewarding, and empowering.

Our ambition is to be one of Canada’s leading and most innovative P&C insurers. Come be a part of our journey, and love what you do.

Starting in September, Definity employees move to a hybrid work model so we can collaborate, build mentoring relationships, and solve complex or cross-functional business opportunities together. Our teams work in whichever environment best supports what they're working on and who they're working with. We're actively reinventing our offices as welcoming workspaces that optimize collaboration and empower leaders to use our space to strengthen team dynamics. Our tools and processes seamlessly connect employees from multiple locations, and our culture encourages respectful engagement and flexibility. Leaders work with their teams to determine the right balance of on-site and remote work that best meets the needs of their team, cross-functional engagement, responsibilities and timelines, plus those of our customers, our broker partners, and the company culture.

This role is an opportunity to join our hybrid team of actuaries and data specialists, solving exciting data science challenges using predictive models, python automation, and a custom SQL Server database. You will rapidly grow your automation & data science skillsets while collaborating on interesting projects including predicting future insurance claim costs and building tools and automated data pipelines to support reserving, planning, and other processes.

Location: Hybrid 

What you can expect in this role?

• Collection and aggregation of both structured and unstructured data from multiple sources
• Maintenance of existing data collection and reporting solutions
• Transformation of datasets to suit modelling, reporting and other purposes
• Construct reporting solutions to develop insights from data
• Perform validation and due diligence checks to assess data integrity
• Procure requested data for the analytics and actuarial teams
• Automate repetitive processes
• Analyze organizational data to recommend solutions to new and complex problems

What do you bring to the role?

• University degree in a quantitative field (e.g. Data Science, Actuarial Sciences, Mathematics, Statistics, Finance/Business)
• Understanding of statistical methods
• Excellent communication and organizational skills
• Experience with Python, SQL, SAS, and/or R

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We also take potential into consideration. If you don’t have this exact experience, but you know you have what it takes, be sure to give us more insight through your application and cover letter.

Go ahead and expect a lot — you deserve it, and we’ve got it: 

• Hybrid work schedule for most roles
• Company share ownership program
• Pension and savings programs, with company-matched RRSP contributions
• Paid volunteer days and company matching on charitable donations
• Educational resources, tuition assistance, and paid time off to study for exams
• Focus on inclusion with employee groups, support for gender affirmation surgery, access to BIPOC counsellors, access to programs for working parents
• Wellness and recognition programs
• Discounts on products and services

Our inclusive work environment welcomes diversity and supports accessibility. If you require accommodation at any time during the recruitment process, please let us know by contacting: [email protected]

Background checks
This role requires successful clearance of a background check (including criminal checks and leadership references).

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