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[Remote] Lead Process Data Consultant II

Remote, USA Full-time Posted 2026-06-17

Note: The job is a remote job and is open to candidates in USA. Skan AI is seeking a seasoned Lead Process Data Consultant to take full ownership of their most strategic customer engagements. This hands-on leadership role focuses on managing complex implementations and ensuring solutions deliver transformational outcomes for enterprise customers.

Responsibilities

  • Own end-to-end responsibility for enterprise-scale implementations—from requirements gathering and process mapping through deployment and performance optimization
  • Take full accountability for project outcomes, timelines, and customer satisfaction across multiple concurrent engagements
  • Configure and customize Skan.ai solutions with meticulous attention to detail, ensuring seamless integration with complex customer environments
  • Serve as the primary technical authority and trusted advisor, proactively identifying risks, resolving blockers, and maintaining momentum
  • Present data-driven insights and strategic recommendations to C-level executives through polished reports, dashboards, and executive briefings
  • Function as a Subject Matter Expert (SME), enabling customer Centers of Excellence (COEs), partners, and internal teams
  • Perform deep-dive analysis of complex process data to uncover inefficiencies, bottlenecks, and high-impact optimization opportunities
  • Conduct rigorous root cause analysis using advanced analytics, statistical methods, and process mining techniques
  • Take ownership of proactive system monitoring, troubleshooting production issues with precision, and managing escalations to ensure zero disruption
  • Roll up your sleeves to solve technical challenges—working directly with Product and Engineering teams to diagnose issues and drive continuous improvement
  • Validate data quality and integrity with meticulous attention to detail
  • Establish and maintain comprehensive documentation of configurations, technical requirements, and process maps to support scalability
  • Create and enforce quality standards and repeatable frameworks that elevate delivery excellence

Skills

  • Bachelor's degree in Engineering, Computer Science, Data Science, or related technical field
  • 8–12 years of progressive experience in consulting, process improvement, or technical delivery roles
  • Deep expertise with process intelligence, process mining, RPA, or BPM platforms (e.g., Celonis, UiPath)
  • Proven track record of owning and delivering complex enterprise projects with measurable business impact
  • Advanced data analysis and interpretation capabilities—statistics, data validation, pattern recognition, and executive reporting
  • Hands-on proficiency with IT systems (Windows, Linux) and web technologies (HTML, CSS, JavaScript)
  • Comfort working in the details—reviewing logs, debugging configurations, and troubleshooting independently
  • Exceptional ability to translate complex process data into clear, actionable business insights that drive executive decision-making
  • Demonstrated ownership mentality—taking full responsibility for outcomes and proactively driving solutions
  • Outstanding project delivery discipline—managing competing priorities and ensuring measurable ROI across multiple engagements
  • Superior communication skills with confidence to engage both technical teams and C-suite leaders
  • Detail-oriented approach with commitment to quality, accuracy, and operational excellence

Company Overview

  • Skan AI is the enterprise system of record for work intelligence, powering AI agents trained on operational reality, not documentation, system logs, or assumptions. It was founded in 2018, and is headquartered in Menlo Park, California, USA, with a workforce of 201-500 employees. Its website is https://www.skan.ai.

Company H1B Sponsorship

  • Skan AI has a track record of offering H1B sponsorships, with 2 in 2025, 1 in 2024, 2 in 2023, 6 in 2022, 2 in 2021. Please note that this does not guarantee sponsorship for this specific role.

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