United States
about 5 hoursAbout Our Client
Our client is a growing SaaS company building critical infrastructure management software for energy, utilities, and telecom operators.
Role Overview
We're looking for a Risk Model Engineer to own the gas distribution risk models within a new AI-driven threat and risk management platform for pipeline asset integrity. Distribution is a new model domain, the threat framework and model set are being defined now in collaboration with subject-matter experts and design-partner operators. You'll help define the models, build them, and take them through validation, producing outputs utilities can use to prioritize replacement programs and support regulatory proceedings. The work focuses on large populations of buried assets with relatively few observed failures, incomplete records, and limited direct inspection data, spanning physics-based probabilistic models and machine learning, with emphasis on risk rankings that remain explainable, calibrated, and defensible. This is a domain-first role, at least one of the two hires needs real hands-on industry experience, with industry knowledge weighing more than specific tooling. No single candidate is expected to check every box below, strength in one area can offset gaps in another.
Key Responsibilities
Translate the gas distribution threat framework, in collaboration with subject-matter experts, into systematic threat identification methods and supporting data structures
Integrate model inputs from diverse datasets across our product offerings
Identify gaps, inconsistencies, and limitations in source data and determine how they should be reflected in model inputs and outputs
Extend threat coverage across gas distribution domains, including legacy material corrosion, plastic embrittlement, excavation damage, cross-bores, and other gas distribution threats
Collaborate closely with ML Ops, data engineering, data science, and subject-matter experts to move models from concept through validated implementation
Produce validation evidence suitable for regulatory, audit, customer, or other formal review
Requirements
Real hands-on experience in gas distribution integrity, operations, consultancy, or regulatory work (at least one of the two hires)
Knowledge of gas distribution integrity management regulations, such as 49 CFR Part 192, Subpart P
No single requirement above is an absolute must-have, strength in one area can offset less depth in another
Nice-to-Have
Gas distribution integrity management program design and replacement prioritization experience, from the operator, consultancy, regulator, or technology-vendor side
Legacy material risk experience (cast iron, bare steel, vintage plastics, plastic embrittlement)
Leak survey, methane detection, and cross-bore program experience
Machine learning applied to physical asset data, trained on sparse or imbalanced events
Python, Databricks, and similar programming or tooling skills (secondary to hands-on domain experience)
Benefits
Competitive salary 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, depending on role and business needs
On-call compensation for eligible on-call shifts
As part of our hiring process, this role may use artificial intelligence or automated tools to assist with reviewing and screening applications. These tools support, but do not replace, human judgment in making hiring decisions.
Your application will only be counted once you complete the full registration process on the KeyStone platform, including creating your profile, uploading your CV, and submitting your application. The AI interview is optional and encouraged, but is not required for your application to be counted.