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Explainable Ai Jobs in Ontario (NOW HIRING)

AI Knowledge Operations Specialist

Toronto, ON ยท On-site

CA$90K - CA$130K/yr

This role ensures the business knowledge is structured, trusted, current, and optimized for AI agent consumption and enabling accurate and reliable, and explainable AI solutions across client ...

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Ultimately, the role helps ensure AI agent capabilities earn and maintain customer trust by delivering consistent, reliable, and explainable outcomes in production. What Will You Do? * Design and ...

Collaborate with Risk, Legal, Compliance, Security, Architecture, and Cloud teams to ensure AI solutions are secure, compliant, explainable, and aligned with enterprise standards. * Support model ...

These capabilities ensure AI solutions remain trusted, explainable, reusable, and production-ready across all Functional Delivery Units (FDUs). The role also defines evaluation and compliance ...

AVP, AI Products & Innovation

Toronto, ON ยท On-site

CA$155K - CA$215K/yr

Partner with Risk, Compliance, Legal, Information Security, Technology, and enterprise AI governance teams to ensure responsible, controlled, auditable, and explainable adoption. Ensure human ...

Manager, Software Engineering

Toronto, ON ยท On-site

CA$140K - CA$170K/yr

Responsible AI & Quality Assurance * Ensure models and systems are explainable, fair, and auditable throughout the solution lifecycle. * Uphold and champion AltaML's Responsible AI (RAI) guidelines ...

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Showing results 1-20

Explainable Ai information

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.

What are the key skills and qualifications needed to thrive as an Explainable AI specialist?

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

What are popular job titles related to Explainable Ai jobs in Ontario?

For Explainable Ai jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Explainable Ai jobs in Ontario look for?

The top searched job categories for Explainable Ai jobs in Ontario are:

Infographic showing various Explainable Ai job openings in Ontario as of August 2026, with employment types broken down into 71% Full Time, 25% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Senior Data Specialist, Enterprise Fraud Analytics

Definity Financial

Toronto, ON โ€ข Hybrid

CA$73K - CA$123K/yr

Full-time

Retirement, PTO

Posted 14 days ago


Job description

The Opportunity

Reporting to the Manager, Enterprise Fraud, the Senior Data Specialist, is a core member of the Enterprise Fraud Analytics team. This role focuses on designing, training, and evaluating advanced machine learning models and predictive analytics to detect and prevent insurance fraud. The candidate will also support Enterprise Fraud strategic priorities and support Fraud Savings initiatives.

Operating in a highly collaborative environment, this role works alongside Business Analysts and the Special Investigations Unit (SIU). The Senior Data Specialist will leverage Google Cloud Platform (GCP) to extract predictive signals from claims, policy, and third-party data and build internal data infrastructure for fraud intelligence and model training. This role is critical in transforming complex fraud detection requirements into robust datasets and extracting predictive signals from structured and unstructured data, ensuring mathematical rigor, sound model evaluation, and explainability of AI solutions.

What to Expect

  • Design, train, and iterate on machine learning models and AI solutions to identify fraudulent behavior and anomalies. Utilize a variety of supervised and unsupervised techniques (e.g., classification, clustering, anomaly detection) on structured and unstructured datasets to build robust fraud detection algorithms. Focus on Natural Language Processing (NLP), Generative AI, and Agentic workflows to extract actionable fraud indicators.
    Conduct rigorous model evaluation (precision, recall, FPR) and threshold tuning. Champion Explainable AI (XAI) by utilizing methods like SHAP values or LLM reasoning traces to ensure model outputs are transparent, interpretable, and trusted by non-technical SIU investigators.
  • Work closely with SIU stakeholders to understand emerging fraud schemes. Conduct in-depth EDA using SQL and Python to assess data feasibility and establish baseline metrics. Design and maintain internal automations and scheduled data retrievals to improve the operational efficiency of the analytics team.
  • Draft technical documentation detailing model architecture, assumptions, limitations, and evaluation metrics. Promote software engineering best practices (version control, CI/CD) and work with compliance teams to ensure AI solutions adhere to data privacy standards (PII/PHI) and algorithmic fairness guidelines.

What you Bring

  • University degree in Computer Science, Data Science, Mathematics, Software Engineering, or a related quantitative discipline. (Master's degree is an asset).
  • 2-5 years of professional experience in a relevant role.
  • Advanced proficiency inย SQLย andย Pythonย (pandas, scikit-learn) for complex data extraction, data processing, and model development.
  • Broad foundational knowledge of machine learning techniques (e.g., tree-based models, regression, clustering, neural networks). Experience with GCP and Vertex AI is a strong asset.
  • Experience withย Natural Language Processing (NLP), text classification, and Large Language Models (LLMs) / prompt engineering.
  • Strong understanding of the ML lifecycle and version control systems.
  • Experience implementing Explainable AI (XAI) techniques to translate complex model decisions to business stakeholders is an asset.
  • Insurance industry knowledge, Fraud Risk Management, and strong business acumen are assets.
  • Strong communication (oral/written) and organizational skills. Bilingual in English/French is an asset.

Salary Range: $73,500-$123,500

Actual salary for the role may vary depending on work location of the successful candidate and other factors including but not limited to, skills, education, experience, working conditions and the local labour market.

This position is being posted to fill an existing vacancy.

Interested in this role, but don't meet every requirement?ย We encourage you to apply! We know from experience that a candidate doesn't need 100% of the qualifications listed to bring incredible value to our team. We're actively seeking diverse backgrounds and perspectives to help us make insurance better. At Definity, inclusion, diversity, and equity aren't just "nice to have" - they're essential to our success.ย 

What's in it for you?

  • Hybrid work schedule for most roles
  • Company share ownership program
  • Incentive Program - Eligible employees may participate in various incentive plans which are paid out at the discretion of the company and subject to individual and company performance.
  • 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 parentsย 
  • Wellness and recognition programsย 
  • Discounts on products and services

Go ahead and expect a lot - you deserve it.

It's better here - but don't take our word for it. Definity was named by Great Place to Work as one of the Best Workplaces in Canada for women, for youth, and for inclusion.

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 contactingย accessibility@economical.com.

As part of Definity's commitment to reconciliation, we acknowledge that our work, meetings, and travel take place on the lands now known as Canada, and recognize the enduring presence, wisdom, and stewardship of the First Nations, Metis, and Inuit peoples who have long cared for these lands.

Background checks

This role requires successful clearance of background checks (including criminal checks and leadership references).

#LI-Hybrid

Definity is the parent company to some of Canada's most long-standing and innovative insurance brands, including Economical Insurance, Sonnet Insurance, Family Insurance Solutions, and Petline Insurance. Our ambition is to be one of Canada's leading and most innovative property and casualty insurers. We can't do that without our people, so we embrace and encourage a culture that's collaborative, ambitious, rewarding, and empowering.ย 

We offer 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. Bring your true self and be a part of our journey. It's better here.ย