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Part Time Data Scientist Machine Learning Jobs in Winnipeg, MB

Wawanesa Insurance

Catastrophe Risk Specialist

Winnipeg, MB · Hybrid

CA$85K - CA$115K/yr

  • Retirement

  • PTO

In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus ... Analyze historical data, scientific research, and insurance claims to enhance model accuracy.

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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

Is it possible to work part-time as a data scientist?

Yes, it is possible to work part-time as a data scientist. Many companies offer flexible schedules or project-based roles that allow data scientists to work fewer hours, especially for freelance or consulting positions. However, full-time roles are more common, and part-time opportunities may require strong self-management and relevant skills in machine learning, programming, and data analysis.

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.

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.

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 most commonly searched types of Data Scientist Machine Learning jobs in Winnipeg, MB?

The most popular types of Data Scientist Machine Learning jobs in Winnipeg, MB are:

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.

Senior AI Platform Developer

The Canada Life Assurance Company

Winnipeg, MB

CA$80K - CA$130K/yr

Full-time, Part-time

Medical, Dental, Life, Retirement

Posted 8 days ago

Job description

Permanent Full Time 

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Canada Life has an ambition to apply human led AI to innovate, elevate customer service, and accelerate growth across the organization. Achieving this ambition requires a secure, scalable, and enterprise grade AI platform that enables teams to build, deploy, and operate AI solutions efficiently and responsibly.

Reporting to the Director, AI Platform Engineering, the Senior AI Platform Developer plays a key role in designing, building, and operating the enterprise AI platform. This role is accountable for developing reusable AI capabilities, shared services, engineering patterns, and platform components that accelerate AI solution delivery while supporting security, reliability, observability, and compliance expectations.

This role provides senior technical leadership, hands on engineering expertise, and mentorship to developers and delivery teams, without requiring formal people management accountability.

What you will do
  • Design, develop, and maintain enterprise AI platform capabilities, services, and reusable technical components.
  • Build shared accelerators, APIs, SDKs, templates, and reference implementations that enable consistent AI solution delivery across the enterprise.
  • Implement platform capabilities for model integration, orchestration, retrieval augmented generation, prompt management, agent frameworks, and model lifecycle support.
  • Develop automation and CI/CD patterns for building, testing, deploying, and operating AI based solutions.
  • Support the integration of AI platforms with enterprise data, identity, security, monitoring, and infrastructure services.
  • Partner with AI solution delivery, architecture, security, cloud, infrastructure, and data teams to onboard and support priority AI use cases.
  • Implement observability, evaluation, telemetry, monitoring, and operational support patterns for AI solutions in production.
  • Contribute to AI engineering standards, platform roadmaps, technical documentation, and reusable design patterns.
  • Evaluate emerging AI technologies and recommend practical enhancements to enterprise platform capabilities.
  • Mentor developers and help raise engineering quality through code reviews, technical guidance, and hands on support.
What you will bring
  • Degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
  • 5 or more years of software engineering experience, with strong hands on development capability.
  • 3 or more years of experience developing AI, machine learning, advanced analytics, or Generative AI solutions.
  • Strong experience with Python, APIs, cloud native development, distributed systems, and modern software engineering practices.
  • Experience with Azure AI Foundry, Azure OpenAI, Databricks, vector databases, model serving platforms, or similar technologies.
  • Experience with DevOps, CI/CD, infrastructure as code, automated testing, and secure software delivery practices.
  • Understanding of AI observability, model evaluation, prompt evaluation, monitoring, and operational support practices.
  • Ability to translate architectural direction into practical, reusable engineering components.
  • Strong collaboration, communication, and problem solving skills in a matrixed environment.
  • Experience in financial services or another regulated industry is an asset.

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The base salary for this position is between $80,400 - $130,400 annually. This represents base salary only and does not represent other variable compensation components of our total compensation ( i.e. annual bonus, commission etc). If you are selected to move forward in our recruitment process, your recruiter will be able to discuss additional details of our total rewards program with you.

Career opportunities will be open a minimum of 5 business days from the date of posting, closing dates will vary depending on the search activity. All applications received will be reviewed on a rolling basis.

Grow with Canada Life 

We're united by a shared purpose: to improve the financial, physical and mental well-being of Canadians. Our company is trusted by 1 in 3 Canadians and contributes to the strength of communities across the country.  

We're looking for people who live our values everyday: we step up, we do the right thing, and we deliver - for our customers, communities and each other. Are you someone who always strives to do the right thing, who steps up for themselves and others, and who delivers with impact? Then we want to hear from you! 

What we offer:  

We're committed to supporting our employees through every stage of their career. Here's what you can expect as a full-time or part-time permanent team member: 

  • Career Development: Opportunities for career advancement, access to industry-leading learning programs and up to$2,000 annually towards education reimbursement. 
  • Health & Wellness:Flexible health and dental benefits, plus a $5,000 mental health benefit to support your well-being. 
  • Time Off:In addition to regular vacation and personal days, we support community involvement with a volunteer day. 
  • Financial Security:Company-matching pension plan,share ownership program and additionalinvestment options. 
  • Rewards and Recognition: Employee recognition programs, service milestone celebrations, employee discounts and more!  
  • Emphasis on Community: We provide a workplace where employees feel connected and supported through Employee Resource Groups (ERGs), mentorship programs, social clubs and events.  

Learn more about Canada Life.  

We're committed to removing barriers and ensuring equal access to employment. Applicants requiring reasonable accommodation during the application process may contact  talentacquisitioncanada@canadalife.com. All information provided will be handled in accordance with applicable laws and Canada Life policies.  

Canada Lifewould like to thank all applicants, however only those who qualify for an interview will be contacted. 

#LI-Hybrid 

Apply