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AI Service Dependency Impact Modeler

Chase Pham

Full-time · Job · Chicago

About the role

When Service X degrades, which other services break, and by how much? At most companies, the answer lives in someone's head. At ours, it should be in a model. We've built the incident management platform that tracks what breaks. What we haven't built is the dependency graph that explains why — and more importantly, the impact predictor that tells on-call engineers which downstream systems to check immediately and which can wait. You'll build the service dependency impact model: mining incident and deployment event logs to infer service dependencies automatically, building the impact propagation model that predicts blast radius from a single service failure, and creating the real-time scoring that surfaces impact predictions during active incidents. The output is a ranked list of services that are likely affected by the current incident, updated as new telemetry arrives. The analytics team is four. You'll own this feature from prototype to production. The senior infrastructure architect who understands the service topology will be your main collaborator for validating model outputs against their domain knowledge.

Responsibilities

  • Mine incident and deployment logs to infer service dependency relationships
  • Build impact propagation model predicting blast radius from service failures
  • Create real-time scoring that updates impact predictions during active incidents
  • Develop confidence calibration for impact predictions used in high-stakes situations
  • Build evaluation framework validating predictions against historical incident records
  • Design APIs integrating impact predictions into the incident management dashboard

Requirements

  • 3+ years in data science or analytics with distributed systems or infrastructure domain experience
  • Experience with graph analysis and network propagation models
  • Strong Python and SQL skills for data pipeline development
  • Understanding of microservice architectures and failure cascade patterns
  • Ability to work with infrastructure engineers to validate model assumptions

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • 401(k) with match
  • $2,500 professional development fund
  • Clear promotion path with semi-annual reviews

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Categories

data science & analytics MLOps & AI Infrastructure

Skills

python sql spark aws statistics

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python sql spark aws statistics pandas

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