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Posted May 18Process Intelligence Senior Specialist
at Autoliv
Bengaluru, Autoliv Asia Aas, United StatesOn-site
Responsibilities
- Execute end-to-end implementations using Celonis process mining, AI, and automation capabilities.
- Ensure a robust data foundation and integration setup to enable scalable and reliable analytics.
- Deliver measurable, value-driven outcomes through process optimization, working capital improvement, and efficiency gains.
- Build and maintain reliable data pipelines to extract, transform, and load data from ERP and enterprise systems into Celonis •
- Develop optimized data models in Celonis to reflect end-to-end business processes and enable process mining insights •
- Monitor and improve data pipeline and model performance, ensuring stability and scalability •
- Implement and maintain data quality checks, validation, and cleansing mechanisms •
- Support process intelligence use cases across global processes (O2C, S2P, OM) •
- Support value discovery workshops and preparation of business insights •
- Develop solutions using Celonis AI features, process copilot, ML Workbench, execution apps, Orchestration engine, annotation builder, and prebuilt applications (e.g., Duplicate Invoice Checker, Sailfin or similar) •
- Build AI-enabled use cases (e.g., anomaly detection, root cause insights, predictive scenarios) •
- Implement automation using Action Flows and orchestration features and integrate with OCR and other automations solutions •
- Maintain technical documentation for data pipelines, models, and transformation logic •
Requirements
- Work with IT and system owners to support data integration from SAP, JDE and other platforms. •
- experience in Celonis Process Mining, ETL, data integration, data modeling, analytics, app development, and automation/orchestration (Action Flows, MLWB, etc.) •
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Analytics, Finance, or related field •
- Strong understanding of Celonis AI capabilities - Process Copilot, ML Workbench, execution apps, and prebuilt applications (end-to-end implementation) •
- Expertise in data modeling, PQL/SQL, Action flows, process mining graphs and analytics/dashboard development •
- Experience with data pipeline development and ETL processes •
- Experience with predictive analytics and process insights (forecasting, anomaly detection, root cause analysis) •
- Understanding of finance processes (O2C, P2P, R2R) •
- Experience in process improvement, analytics, or transformation environments •
- Experience with SQL and scripting languages (e.g., Python ) is preferred •
- Willingness to learn and work across multiple areas of value-driven data and analytics, utilizing Power BI, Snowflake, and related technologies •
- Ability to manage multiple tasks and deliver in a fast-paced environment •
Additional details
- We are working to increase vehicle safety by developing seatbelts, airbags and steering wheels and you can be part of our team as Process Intelligence Senior Specialist .
- Our COE team is on a mission to improve business outcomes and employee experiences by driving step-change improvements in critical enterprise processes, and the technology and analytics supporting these.
- We are seeking a Process Intelligence Senior Specialist ( Celonis ) to join our Process Intelligence COE Team.
- This role is responsible for designing, building, and supporting Celonis-based process intelligence solutions across global finance processes.
- If you will be able to manage the following key responsibilities: •
- Collaboration & Partner with business process SMEs, value engineers, and process owners to understand process requirements, translate them into data models, and provide technical guidance for building value‑driven use cases. •
- Adhere to data governance, compliance, and internal standards •
- Continuously learn and apply new Celonis and data engineering capabilities and if you have: • 4–7 years of proven
- Strong stakeholder collaboration in a global and cross-functional environment •
- Strong analytical mindset with attention to data quality and accuracy •