DIMP Model Engineer

Posted 5 days ago

This is a fully remote position, open to applicants in Canada, +1 more country.

πŸ“‹ Description

β€’ Take ownership of gas distribution risk models within Irth’s analytical framework.

β€’ Collaborate with subject-matter experts and design-partner operators to establish gas distribution threat frameworks and model sets.

β€’ Develop risk models and guide them through the validation process.

β€’ Generate explainable, calibrated, and justifiable risk rankings for utility replacement programs and regulatory proceedings.

β€’ Manage model content, detailing what the model calculates, the rationale behind it, and the evidence supporting its validity.

β€’ Convert the gas distribution threat framework into systematic methods for threat identification and supporting data structures.

β€’ Integrate model inputs from various datasets across Irth’s product offerings.

β€’ Detect gaps, inconsistencies, and limitations in source data, and assess how they should be represented in model inputs and outputs.

β€’ Broaden threat coverage to include legacy material corrosion, plastic embrittlement, excavation damage, cross-bores, and other gas distribution threats.

β€’ Work closely with dedicated ML Ops and data engineering teams responsible for model serving, data pipelines, deployment, and monitoring infrastructure.


⛳️ Requirements

β€’ Relevant experience in gas distribution integrity management, encompassing program design, threat identification as per 49 CFR Part 192, Subpart P, and replacement prioritization.

β€’ Familiarity with legacy material risks, including cast iron, bare steel, vintage plastics, and plastic embrittlement.

β€’ Experience with leak survey, methane detection, and cross-bore programs.

β€’ Application of machine learning to physical asset data, including time-series, survival, anomaly-detection, and classification models.

β€’ Strong expertise in one or more pertinent capability areas.

β€’ Curiosity and judgment to collaborate across different capability areas.

β€’ Ability to work with subject-matter experts, ML Ops, and data engineering teams.


🏝️ Benefits

β€’ Competitive compensation package based on experience and qualifications.

β€’ Medical, Dental, and Vision Insurance.

β€’ 401(k) Plan with Company Match.

β€’ Generous Paid Time Off (PTO).

β€’ Company-Paid Holidays.

β€’ Flexible Work Options / work-from-home opportunities, depending on role and business needs.

β€’ On-Call Compensation for eligible on-call shifts.

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