Machine Learning Operationalization (MLOps) Analyst

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.

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.

Role Location: Waterloo or Toronto (Hybrid - 20% to 40% in office)

The Advanced Analytics team at Definity is looking for an individual with a passion and expertise in the area of Machine Learning Operationalization (MLOps). As an MLOps Analyst reporting to the Manager, Advanced Analytics, you will be responsible for supporting the operationalization of complex analytical solutions, and the monitoring & improvement of the underlying machine learning models, so that we sustain the benefits of the solutions to the organization and to our customers.

What can you expect in this role?

• You will operationalize Analytical solutions (API’s, batch processes, analytical applications), and be able to contribute to the development of new solutions and improvement of existing solutions.
• You will bring new ideas to contribute to innovation and process improvement.
• You will work with Data Scientists within our team, our business stakeholders and other technical teams to deliver Analytical solutions to the business – we believe strongly in working together to deliver business value versus throwing a model over the fence to be operationalized.

What do you bring to this role?

• University degree in Software Engineering, Computer Science, Data Science or a related discipline
• 2-4 years in developing and operationalizing analytical solutions
• Highly analytical, demonstrated ability to develop creative solutions to complex problems
• Strong proficiency with R or Python
• Experience with model drift monitoring and refresh automation
• Experience with Google Cloud for MLOps is an asset

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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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