Modelling and Advanced Analytics Co-op
This job posting is no longer active.
Job ID : 5716
Category : Personal Insurance
Brand : Definity
Regular/Temporary : Temporary
Fulltime/Parttime : Full Time
Location : Waterloo, Canada
Definity 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, we’ve 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.
Definity offers a flexible, hybrid work experience where employees work from the office and virtually depending on the type of work they are doing and who they are working with. Leaders partner with their teams to find the right balance of on-site and remote work that best meets the needs of their teams, colleagues, brokers and customers, while ensuring collaboration, teamwork and accountability for goals.
What can you expect in this role?
Reporting to a Modelling & Pricing Analytics Manager, you will play a key role in contributing to the pricing and insurance projects using state of the art models and innovative approaches. If you’re a data scientist, statistician, mathematician or actuary who is passionate about modelling and advanced analytics, this is a great opportunity to learn how true actuarial operations work in an innovative company.
About the role:
- Develop knowledge of actuarial operations and the insurance business, including predictive modelling, underwriting, claims handling, and product development
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Develop experience with databases and statistical software to prepare and analyze data used in pricing, modelling, profitability analysis and other diverse applications
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Contribute to the support, management and monitoring of models throughout the model lifecycle
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Learn to communicate data and modelling concepts to others both verbally and in writing
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Respond to requests of internal and external stakeholders with support from more senior staff
What do you bring to the role?
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Currently enrolled in a university degree in Actuarial Sciences, Mathematics, Statistics, Software Engineering, Computer Science, Data Science or other related fields
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Must possess strong programming skills, including knowledge of Python, R and/or SQL
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Knowledge of machine learning techniques like GLM, GAM, XGBoost, Neural Networks, k-NN and SVM is an asset
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Knowledge of Git for version control and collaboration, APIs, agile methodologies and/or Sharepoint is an asset
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Work Location: the position will either be a hybrid (1-3 days in office) or fully remote. These positions are spread across our different locations including Kitchener/Waterloo, Mississauga and Toronto
How to apply: Submit a cover letter, resume, most recent copy of an unofficial transcript and 1 letter of reference in one document
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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