Model Risk Management Manager leading model validation, governance and risk oversight at Export Development Canada. Advising senior stakeholders across financial and advanced analytics models.
About the role
- Risk Model Engineer migrating and validating probabilistic pipeline integrity models for Irth Solutions’ AI-driven risk platform. Extending transmission threat coverage through machine learning, geospatial analysis, and defensible reliability assessments.
Responsibilities
- Migrate existing probabilistic model code to the new risk management platform
- Validate results against current production implementations
- Integrate model inputs from diverse datasets across Irth’s product offerings
- Extend threat coverage across transmission pipeline integrity domains, including corrosion, cracking, third-party damage, and outside forces
- Design and build time-series, anomaly detection, and geospatial models using inspection, sensor, maintenance, and related data
- Implement industry-standard probabilistic risk models within the analytical layer
- Support customer-driven model development on the platform
- Develop, evaluate, and present sensitivity analyses for model offerings
- Validate model outputs against customer data, known outcomes, and regulatory expectations
- Partner daily with ML Ops and data engineering teams while owning model methodology, content, validation, and supporting evidence
Requirements
- Practical North American oil and gas transmission experience is the highest priority
- Experience with North American oil and gas transmission integrity management
- Knowledge of applicable standards and regulations such as ASME B31.8S, 49 CFR 192, CSA Z662, or equivalents
- Familiarity with fitness-for-service, remaining-strength assessments, corrosion growth modeling, or fracture mechanics
- Experience with in-line inspection (ILI) vendor data formats, data alignment, anomaly classification, and feature disposition
- Experience with high-consequence areas, class-location analysis, or related pipeline risk assessment requirements
- Experience preparing technical documentation and validation evidence for regulatory review, audits, or formal assessments
- Experience building or validating risk, reliability, or failure models for physical infrastructure
- Familiarity with Monte Carlo simulation, structural reliability, uncertainty quantification, or related probabilistic methods
- Experience applying machine learning to time-series, survival, anomaly detection, or classification problems involving physical asset data
- Experience training and validating models on sparse, imbalanced failure events is particularly valuable
- Experience with ArcGIS, PostGIS, linear referencing, or geospatial risk assessment
- Python and sound software engineering practices, including testing, code review, reproducibility, and disciplined use of AI coding assistants
- Comfort working with incomplete, inconsistent, and imperfect data
- Ability to distinguish a defensible, validated model from one that simply produces a number
Benefits
- Competitive compensation package based on experience and qualifications
- Medical, Dental, and Vision Insurance
- 401(k) Plan with Company Match
- Generous Paid Time Off (PTO)
- Company-Paid Holidays
- Flexible Work Options / work-from-home opportunities
- On-Call Compensation for eligible on-call shifts
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