Job
Description
About The Role
S&C GN - MC - Industry X - Intelligent Asset Management – Consultant
Industrial AI Consultant - Maintenance & Reliability
7–8 years
Location focus: India / Argentina / Kuala Lumpur
Reporting: Reports to Senior Manager / Associate Director (no direct reports, but expected to mentor junior analysts)
Team context: Embedded within Strategy & Consulting; leads client modules in partnership with functional consultants and data science teams.
Role
Summary
As a Consultant you will play an expanded role in shaping client engagements "” from identifying business opportunity to driving pilots toward scaled deployments. This role requires stronger strategic thinking, proven delivery experience on asset-intensive AI projects, and the ability to create commercial value cases and executive presentations while remaining deeply hands-on with data science and architecture. You will lead AI initiatives including LLMs, AI agents/copilots, predictive analytics and operational AI solutions integrated into industrial workflows. Key Responsibilities
Lead client conversations to define strategic objectives, create prioritization frameworks, and co-design AI-enabled maintenance strategies. Identify and develop AI use cases across asset management areas (reliability, predictive analytics, maintenance optimization), including building and scaling AI agents/copilots that enhance operational workflows. Own the end-to-end delivery of analytics use cases (PoC ’ pilot ’ scale) in asset management, ensuring alignment to business KPIs and value realization. Architect data solutions in collaboration with data engineering and IT (data models, ingestion patterns, cloud/edge considerations, integration with EAM/CMMS/historians). Develop and quantify business cases (financial impacts, KPIs, TCO) and support proposal development and commercial negotiations. Mentor and review work of junior analysts; provide technical and consulting guidance to ensure delivery quality. Lead stakeholder engagement with plant operations, maintenance leadership and executive sponsors; present findings in client workshops and steering committees. Ensure best practices for responsible AI, governance, and cybersecurity are embedded in solutions. Support model deployment, monitoring, and lifecycle management (MLOps, MLflow, Airflow). Contribute to capability building:training, playbooks, reusable accelerators and thought leadership.
Qualification
Must-have
Qualifications & Skills
B.Tech / BE (mandatory); MBA or equivalent in analytics/management preferred.
7–8 years' experience with proven delivery of analytics/AI projects in manufacturing or other asset-intensive industries (predictive maintenance, reliability, OEE improvement).
Hands-on proficiency in Python/similar and SQL; experience producing reusable modelling pipelines and productionizing models.
Strong understanding of enterprise data architectures, cloud platforms, Azure, Databricks or equivalent, and integration with EAM/CMMS (SAP PM, Maximo) and historians.
Experience quantifying business impact and building financial/ROI models for analytics initiatives.
Experience identifying and developing AI use cases across asset management domains and implementing AI agents/copilots to enhance workflows.
AI/ML Techniques: time-series forecasting, anomaly detection, NLP, predictive modeling.
Deployment & MLOps: model deployment, monitoring, lifecycle management (MLflow, Airflow, etc.).
GenAI / LLM exposure: prompt engineering, retrieval-augmented generation (RAG), AI agents frameworks understanding.
Excellent stakeholder management and executive presentation skills; experience leading workshops and steering committees.
Solid grounding in maintenance practices (condition monitoring, RCM/RCA/FMEA) and operational excellence concepts.
English Fluency (mandatory)
Nice to have:Familiarity with IIoT platforms, edge analytics, and OPC/PLC integration.
Cloud certifications (Azure / AWS / GCP) or reliability engineering certifications.
Experience with advanced visualization or analytics tools beyond standard reporting.
Behavioral Competencies
Strategic thinker with strong commercial acumen and ability to translate technical outputs into executive actions.
Confident client presence; able to influence senior stakeholders.
Mentorship orientation and proven ability to raise team capability.
