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Manager, Advanced Analytics

Remote / Online - Candidates ideally in
Winnipeg, Manitoba, A3C, Canada
Listing for: Wawanesa
Full Time, Part Time, Remote/Work from Home position
Listed on 2026-06-16
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 140000 - 180000 CAD Yearly CAD 140000.00 180000.00 YEAR
Job Description & How to Apply Below

Job

9789

Employment Type

Existing Role

Working Business Language

English

Salary & Compensation

Salary:
At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus plan, leave of absence top-up programs and provided with generous vacation time, personal days, premium free benefits and pension plan.

The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $140,000 - $180,000. Candidates with salary expectations outside of the range are still encouraged to apply.

About Us

At Wawanesa, we offer a hybrid work environment that offers flexibility to our employees in balancing in-office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work.

You may work from any of the following locations:
Winnipeg, MB;
Calgary, AB;
Toronto (North York), ON.

The Wawanesa Mutual Insurance Company (“Wawanesa Mutual”), founded in 1896, is one of Canada’s largest mutual insurers, with over $3.5 billion in annual revenue and assets of $10 billion (CAD). Wawanesa Mutual, with its National Headquarters in Winnipeg, is the parent company of Wawanesa Life, which provides life insurance products and services throughout Canada, and Western Financial Group, which distributes personal and business insurance across Canada.

Wawanesa proudly serves more than 1.7 million members in Canada, and we are home to more than 3,300 employees distributed across the Canadian regions and communities where we operate. We give back to organizations that strengthen communities, donating more than $3.5 million annually to charitable organizations, including over $2 million annually in support of people on the front lines of climate change.

We are also proud to be recognized as one of Manitoba’s Top Employers. To learn more visit

We are currently looking for dedicated, driven, and enthusiastic individuals who thrive in an environment that welcomes change and are looking for an opportunity for diverse experience and advancement on a growing team.

Job Overview

The Manager of Advanced Analytics contributes to Wawanesa’s success by bringing your passion for predictive modeling and machine learning. In this role, you will lead the Machine Learning Operations (MLOps) function, ensuring scalable, reliable, and cost-effective deployment of machine learning solutions across the enterprise. The manager is leading a team responsible for taking machine learning applications to support decision making across the organization from concept to production, with accountability for platform architecture, production reliability, governance, and lifecycle management.

Job Responsibilities
  • Work directly with organizational leaders to introduce advanced analytics to all functions within the organization, and to foster the advancement and adoption of analytic assets.
  • Develop and advance analytic standards and processes that enable all aspects of advanced analytics including applied research, proof of concept, deployment of production grade ethical machine learning models, model monitoring and measurement.
  • Own and evolve the enterprise MLOps platform strategy, including CI/CD for ML, model registry, feature management, orchestration, monitoring, and observability frameworks.
  • Establish standardized deployment patterns and infrastructure-as-code practices to reduce bespoke solutions and increase reuse across teams.
  • Model lifecycle governance from development through validation, deployment, monitoring, retraining, and retirement.
  • Identify and organize educational initiatives aimed at the development of overall inter- and intra-departmental knowledge.
  • Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.
  • Perform other duties as assigned.
Qua…
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