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AI Process Mining Engineer

Mason Oliveira

Full-time · Job · Chicago

About the role

Enterprise operations generate millions of event logs — every click, approval, handoff, and delay captured in system audit trails. Process mining turns these logs into visual process maps that reveal how work actually flows, where bottlenecks hide, and which process variants waste the most time. You'll build the AI layer on top of our process mining platform: automated bottleneck detection, conformance checking that flags deviations from intended workflows, and predictive models that estimate case completion times based on early-stage process signals. We work with operations teams at 8 logistics companies. The process data is messy — timestamps from different systems don't align, event names are inconsistent, and some activities are logged in one system but not another. Half your job is making sense of chaotic event data before any analysis can begin.

Responsibilities

  • Build automated bottleneck detection from enterprise event log data
  • Design conformance checking systems for workflow deviation analysis
  • Develop predictive models for case completion time estimation
  • Clean and harmonize event logs from heterogeneous enterprise systems
  • Create process visualization dashboards for operations teams

Requirements

  • 3+ years in data engineering or process analytics
  • Strong Python and SQL skills for event log processing
  • Experience with time series analysis and pattern detection
  • Familiarity with process mining concepts and tools
  • Comfort working with messy, inconsistent enterprise data

Benefits

  • Fully remote — US Central time zone
  • Health insurance
  • $2,000 learning budget
  • Direct impact on operational efficiency for logistics clients

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

Automation & AI Workflows data science & analytics

Skills

python sql pandas scikit-learn airflow docker

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