Overview The PSR SME owns the design and delivery of the Product & Service Record data model — the authoritative representation of how CUSTOMER's network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.

Key Responsibilities
PSR Model Design
• Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
• Define PSR entities, attributes, relationships, and hierarchies.
• Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
• Validate model against current Catalog, Inventory and Ordering systems. Source System Analysis
• Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
• Map data lineage from source systems to PSR model.
• Raise structured data requests to CUSTOMER stakeholders. Stakeholder & Workshop Engagement
• Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
• Align with CMDB SME on CI-to-product mapping.
• Present findings and model designs to programme leadership. Use Case Enablement
• Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
• Support event correlation and service impact design. Programme Delivery
• Author workstream deliverables; maintain RAID log.
• Contribute to JIRA stories and sprint planning. Ensure delivery aligns to PI features and sprint goals. Key Deliverables 1 Generic PSR Data Model Product-agnostic entities, attributes & relationships. 2 CUSTOMER-Specific PSR Models Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data. 3 PSR Attribute Specification Sheet Attribute detail: type, source, transformation rule, mandatory flag. 4 Source System Analysis Report Current Catalog, Inventory and Ordering systems — schemas, gaps, quality findings. 5 Data Lineage Map (PSR) Source-to-PSR traceability for all key data attributes. 6 PSR–CMDB Integration Design How PSR entities map to CMDB CI classes. 7 Use Case Data Requirements Data needs per AI Ops use case at each delivery layer. 8 Gap Analysis & Recommendations Current state vs. PSR model requirements with prioritised actions. 9 PSR Workstream RAID Log Ongoing risks, assumptions, issues, and dependencies. Skills & Experience Domain Knowledge
• Telecom product & service structures (MPLS, IP Connect, SD-WAN).
• Product catalogue and service inventory data models in a telco OSS/BSS context.
• Network provisioning and fulfilment systems (billing gateways, order management).
• CMDB data models and CI class design — ServiceNow preferred.
• AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
• Service assurance and fault management in network operations. Technical Skills
• Data modelling — entity-relationship, conceptual, logical, physical.
• SQL / database querying for schema analysis and validation.
• Data mapping and transformation specification writing.
• Ability to read and interpret complex, under documented database schemas.
• JIRA — user story creation and sprint tracking.
• TMF SID certification
- desirable
• ServiceNow (ITSM, CMDB, Event Management) — desirable.
• Kafka / event streaming awareness — desirable. Behavioural & Consulting
• Stakeholder engagement — extracting requirements from time-poor CUSTOMER SMEs.
• Structured problem-solving in data-poor, ambiguous environments.
• Persistence in accessing and validating data from complex legacy systems.
• Clear communication — presenting data models to technical and non-technical audiences.
• Proactive risk identification and escalation. Comfortable with iterative, agile delivery and progressive elaboration.



Responsibilities The PSR SME owns the design and delivery of the Product & Service Record data model — the authoritative representation of how CUSTOMER's network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.

Key Responsibilities
PSR Model Design
• Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
• Define PSR entities, attributes, relationships, and hierarchies.
• Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
• Validate model against current Catalog, Inventory and Ordering systems. Source System Analysis
• Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
• Map data lineage from source systems to PSR model.
• Raise structured data requests to CUSTOMER stakeholders. Stakeholder & Workshop Engagement
• Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
• Align with CMDB SME on CI-to-product mapping.
• Present findings and model designs to programme leadership. Use Case Enablement
• Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
• Support event correlation and service impact design. Programme Delivery
• Author workstream deliverables; maintain RAID log.
• Contribute to JIRA stories and sprint planning. Ensure delivery aligns to PI features and sprint goals. Key Deliverables 1 Generic PSR Data Model Product-agnostic entities, attributes & relationships. 2 CUSTOMER-Specific PSR Models Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data. 3 PSR Attribute Specification Sheet Attribute detail: type, source, transformation rule, mandatory flag. 4 Source System Analysis Report Current Catalog, Inventory and Ordering systems — schemas, gaps, quality findings. 5 Data Lineage Map (PSR) Source-to-PSR traceability for all key data attributes. 6 PSR–CMDB Integration Design How PSR entities map to CMDB CI classes. 7 Use Case Data Requirements Data needs per AI Ops use case at each delivery layer. 8 Gap Analysis & Recommendations Current state vs. PSR model requirements with prioritised actions. 9 PSR Workstream RAID Log Ongoing risks, assumptions, issues, and dependencies. Skills & Experience Domain Knowledge
• Telecom product & service structures (MPLS, IP Connect, SD-WAN).
• Product catalogue and service inventory data models in a telco OSS/BSS context.
• Network provisioning and fulfilment systems (billing gateways, order management).
• CMDB data models and CI class design — ServiceNow preferred.
• AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
• Service assurance and fault management in network operations. Technical Skills
• Data modelling — entity-relationship, conceptual, logical, physical.
• SQL / database querying for schema analysis and validation.
• Data mapping and transformation specification writing.
• Ability to read and interpret complex, under documented database schemas.
• JIRA — user story creation and sprint tracking.
• TMF SID certification
- desirable
• ServiceNow (ITSM, CMDB, Event Management) — desirable.
• Kafka / event streaming awareness — desirable. Behavioural & Consulting
• Stakeholder engagement — extracting requirements from time-poor CUSTOMER SMEs.
• Structured problem-solving in data-poor, ambiguous environments.
• Persistence in accessing and validating data from complex legacy systems.
• Clear communication — presenting data models to technical and non-technical audiences.




• Proactive risk identification and escalation. Comfortable with iterative, agile delivery and progressive elaboration. Requirements The PSR SME owns the design and delivery of the Product & Service Record data model — the authoritative representation of how CUSTOMER's network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.

Key Responsibilities
PSR Model Design
• Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
• Define PSR entities, attributes, relationships, and hierarchies.
• Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
• Validate model against current Catalog, Inventory and Ordering systems. Source System Analysis
• Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
• Map data lineage from source systems to PSR model.
• Raise structured data requests to CUSTOMER stakeholders. Stakeholder & Workshop Engagement
• Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
• Align with CMDB SME on CI-to-product mapping.
• Present findings and model designs to programme leadership. Use Case Enablement
• Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
• Support event correlation and service impact design. Programme Delivery
• Author workstream deliverables; maintain RAID log.
• Contribute to JIRA stories and sprint planning. Ensure delivery aligns to PI features and sprint goals. Key Deliverables 1 Generic PSR Data Model Product-agnostic entities, attributes & relationships. 2 CUSTOMER-Specific PSR Models Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data. 3 PSR Attribute Specification Sheet Attribute detail: type, source, transformation rule, mandatory flag. 4 Source System Analysis Report Current Catalog, Inventory and Ordering systems — schemas, gaps, quality findings. 5 Data Lineage Map (PSR) Source-to-PSR traceability for all key data attributes. 6 PSR–CMDB Integration Design How PSR entities map to CMDB CI classes. 7 Use Case Data Requirements Data needs per AI Ops use case at each delivery layer. 8 Gap Analysis & Recommendations Current state vs. PSR model requirements with prioritised actions. 9 PSR Workstream RAID Log Ongoing risks, assumptions, issues, and dependencies. Skills & Experience Domain Knowledge
• Telecom product & service structures (MPLS, IP Connect, SD-WAN).
• Product catalogue and service inventory data models in a telco OSS/BSS context.
• Network provisioning and fulfilment systems (billing gateways, order management).
• CMDB data models and CI class design — ServiceNow preferred.
• AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
• Service assurance and fault management in network operations. Technical Skills
• Data modelling — entity-relationship, conceptual, logical, physical.
• SQL / database querying for schema analysis and validation.
• Data mapping and transformation specification writing.
• Ability to read and interpret complex, under documented database schemas.
• JIRA — user story creation and sprint tracking.
• TMF SID certification
- desirable
• ServiceNow (ITSM, CMDB, Event Management) — desirable.
• Kafka / event streaming awareness — desirable. Behavioural & Consulting
• Stakeholder engagement — extracting requirements from time-poor CUSTOMER SMEs.
• Structured problem-solving in data-poor, ambiguous environments.
• Persistence in accessing and validating data from complex legacy systems.
• Transparent communication — presenting data models to technical and non-technical audiences.
• Proactive risk identification and escalation. Comfortable with iterative, agile delivery and progressive elaboration.

📌 PSR Modeler (Chennai)
🏢 Prodapt
📍 Chennai