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Part Time Data Scientist Machine Learning Jobs in Winnipeg, MB

Wawanesa Insurance

Actuarial Intern

Winnipeg, MB · Hybrid

CA$26.53/hr

In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus ... Data Collection * Research, extract, and manipulate complex data from relevant sources * Identify ...

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All JobsData Scientist Machine Learning JobsPart Time Data Scientist Machine Learning JobsPart Time Data Scientist Machine Learning Jobs in Winnipeg, MB

Part Time Data Scientist Machine Learning information

What does a part time data scientist specializing in machine learning do?

A part time data scientist with a focus on machine learning uses statistical methods and algorithms to analyze data and build predictive models, typically on a flexible or reduced schedule. They work with datasets to extract insights, clean and prepare data, train machine learning models, and help organizations make data-driven decisions. Their responsibilities may include collaborating with teams, presenting findings, and deploying models, but on a part-time basis, allowing for work-life balance or the pursuit of additional projects. This role is ideal for those seeking to contribute their expertise without committing to a full-time position.

What are the key skills and qualifications needed to thrive as a part time data scientist machine learning?

To thrive as a Part Time Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch, as well as experience with data visualization tools and cloud platforms, is highly valued. Strong analytical thinking, problem-solving abilities, and effective communication skills help you translate complex data insights for stakeholders and collaborate within teams. These competencies ensure you can develop accurate models, deliver actionable results efficiently, and adapt to the dynamic needs of part-time project work.

How do part time data scientists specializing in machine learning typically collaborate with full-time teams and stakeholders?

Part-time data scientists in machine learning roles often work closely with full-time team members through regular meetings, collaborative project management tools, and clear documentation. They may be responsible for specific components of a project, such as data preprocessing, model development, or evaluation, and are expected to provide frequent updates and integrate their work with the broader team’s efforts. Effective communication and proactive time management are key, as part-time professionals usually need to balance their limited hours with project milestones and cross-functional collaboration. This structure allows part-time data scientists to contribute significant value while maintaining flexibility.

What is the difference between Part Time Data Scientist Machine Learning vs Part Time Data Analyst?

AspectPart Time Data Scientist Machine LearningPart Time Data Analyst
Required CredentialsDegree in Data Science, Computer Science, or related field; knowledge of machine learning algorithmsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and basic analytics
Work EnvironmentFocus on developing predictive models, machine learning algorithms, and advanced analyticsData cleaning, reporting, and descriptive analysis of datasets
Employer & Industry UsageTech companies, finance, healthcare, and industries leveraging AI and predictive analyticsRetail, marketing, finance, and other sectors requiring data reporting and insights

Part Time Data Scientist Machine Learning roles focus on building predictive models and applying machine learning techniques, requiring specialized skills and advanced knowledge. In contrast, Part Time Data Analysts primarily handle data cleaning, reporting, and descriptive analysis. Both roles are essential but differ in complexity and technical depth.

Part Time Data Scientist Machine Learning jobs near you
Infographic showing various Part Time Data Scientist Machine Learning job openings in Winnipeg, MB as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Director, Direct Venture Pricing

Wawanesa Insurance

Winnipeg, MB • Hybrid

CA$170K - CA$220K/yr

Full-time, Part-time

Retirement, PTO

Posted 9 days ago

Job description

Job ID: 10284 


Employment Type: New Role 

Work Environment: 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; Vancouver, BC; Calgary, AB; Edmonton, AB; Toronto (North York), ON; Kitchener, ON; Ottawa, ON; Montreal, QC; Quebec City, QC, Moncton, NB; Dartmouth; NS. 

Working Business Language: English. This role is considered a head-office role and will be required to communicate with internal stakeholders across Canada where the primary business language utilized is English
 

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: $170,000- $220,000.  Candidates with salary expectations outside of the range are still encouraged to apply. 

About The Wawanesa Mutual Insurance Company
Founded in 1896, The Wawanesa Mutual Insurance Company is one of Canada's largest mutual insurers, 100% owned by its members, with more than $4.1 billion in annual revenue and $12.5 billion in assets. Headquartered in Winnipeg, Wawanesa is the parent company of Wawanesa Life, which provides life insurance solutions throughout Canada, and Western Financial Group, a leading national distributor of personal and business insurance. In March of 2026, Wawanesa entered into an agreement to acquire Everest Insurance Company of Canada to strengthen its commercial insurance capabilities and advance its long-term growth strategy.


Wawanesa proudly serves more than 1.8 million members and we are home to more than 3,000 employees across Canada. The company actively gives back to organizations that strengthen communities, donating more than $4 million annually to charitable organizations, including more than $2 million each year in support of people on the front lines of climate change. Learn more at wawanesa.com.

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 Director, Direct Venture Pricing leads the Direct-to-Member (D2M) pricing strategy and builds a pricing capability that supports sustainable profitability, competitive positioning, and member value. In a start-up environment, the role advances sophisticated pricing, analytics, and modeling practices for a direct-digital, AI-native business.


Partnering across Product, Underwriting, Claims, Marketing, Data Science, Technology, Finance, Regulatory Affairs and other Business Lines, the Director owns technical pricing, segmentation, rate-level management, and pricing frameworks. The role advises senior leaders and balances profitability, member outcomes, regulation, and business objectives across the product portfolio.

Job Responsibilities
  • Own D2M portfolio financial performance across insurance and non-insurance products by setting and executing pricing strategy, roadmap, and rate actions aligned with the business plan and market conditions.
  • Lead advanced pricing models and methodologies using AI, predictive analytics, machine learning, and emerging data; incorporate cross-sell, bundling, and cross-subsidization across the product suite.
  • Establish pricing-model governance, including validation, monitoring, documentation, compliance, risk management, and performance oversight.
  • Partner with Product, Underwriting, Finance, Marketing, Claims, Technology, Data & Analytics and collaborate with other Business Lines as needed, to embed pricing insights in decisions and optimize portfolio performance.
  • Monitor portfolio results, member research, market and competitor activity, regulation, and industry trends; identify risks and opportunities and recommend timely action.
  • Develop pricing proposals and business cases supported by rigorous analysis; ensure pricing changes comply with provincial and federal insurance requirements.
  • Advise and influence senior leaders, facilitate cross-functional alignment, and lead strategic pricing initiatives from concept through implementation and benefits realization.
  • Build and lead a high-performing pricing team through talent attraction, coaching, development, and retention; foster innovation, accountability, technical excellence, collaboration, continuous learning, and profitable growth.
Qualifications
  • Minimum 10 years of insurance pricing experience across multiple lines of business, including at least three years in leadership. Start-up, advanced analytics, non-insurance pricing, or Life insurance experience is an asset.
  • Undergraduate degree in Actuarial Mathematics, Statistics, Mathematics, Commerce, Economics, or a related field. ACAS, FCAS, or equivalent actuarial designation strongly preferred; MBA, CIP, FCIP, or another relevant designation is an asset.
  • Deep expertise in P&C products, pricing, underwriting, insurance operations, regulation, advanced statistical modeling, AI, predictive analytics, and model governance.
  • Strong business acumen, analytical judgment, and problem-solving; able to identify critical issues, make sound decisions under pressure, and translate analysis into action.
  • Proven ability to lead strategy and transformation, influence complex decisions, build credibility and stakeholder relationships, and communicate effectively in writing, presentations, and discussion.
  • Intrapreneurial and innovative; resilient, adaptable, and strategically minded; comfortable in a fast-paced environment; communicates a compelling vision, proactively identifies opportunities, and drives measurable results.


Diversity Equity, Inclusion& Belonging
At Wawanesa, we are committed to Diversity, Equity, Inclusion and Belonging (DEIB) and believe that our strength lies in the diversity of our people - this is supported by having a representative workforce.

We welcome applications from all qualified candidates, including racialized persons, women, Indigenous Peoples, persons with disabilities, members of the 2SLGBTQIA+ community, gender-diverse and neurodiverse individuals, and anyone who can contribute to the further diversification of thought and ideas. 
 

We aim to ensure our recruitment process is accessible to all candidates. If you require accommodations during any stage of the recruitment process, please reach out in confidence to jobs@wawanesa.com.
 

All Wawanesa job applicants are subject to Wawanesa's Privacy Policy.

Please note that the recruitment process for this position may involve the use of AI tools to screen, assess, or select applicants. All final decisions are taken or reviewed by human recruiters and human hiring leaders in compliance with all applicable legislation.  
 

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