Autonomous Network AI Scientist: KPI & Graph Analytics

CAPGEMINI; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Capgemini is seeking an AI Data Scientist to apply data science, statistics, ML, graph analytics, and KPI engineering to enable autonomous network intelligence. You will work with network telemetry, topology, inventory, and service data to develop analytical insights and predictive intelligence for autonomous network operations.

The role involves building models for anomaly detection, fault prediction, and proactive assurance, plus developing data pipelines and TMF‑aligned data models.

Qualifications

• Experience in data science, telecommunications analytics, network performance analytics, or AIOps analytics.
• Strong Python skills for data analysis, modelling, and automation.
• Solid understanding of statistics, ML basics, feature engineering, and model evaluation.
• Experience with network KPIs, alarms, telemetry, inventory, topology, or service assurance data.
• Understanding of telecom network domains including RAN, Core, IP/MPLS, SD‑WAN, Transport, Cloud, or OSS.

Responsibilities

• Analyse large-scale telecom network datasets across RAN, Core, IP, Transport, SD‑WAN, Cloud, OSS, and service domains.
• Develop KPI engineering models for network performance, service quality, fault behaviour, customer impact, capacity, and resilience.
• Build statistical and machine learning models for anomaly detection, fault prediction, root-cause analysis, degradation detection, and proactive assurance.
• Develop data aggregation, cleansing, enrichment, and feature engineering pipelines for network telemetry and OSS data.
• Support digital twin analytics using topology, inventory, configuration, service dependency, performance, and fault data.
• Develop graph analytics models for network topology, entity relationships, dependency mapping, service impact, and fault propagation.
• Work with AI/LLM engineers to provide high-quality features, embeddings, metadata, and contextual datasets for RAG and agentic AI systems.
• Define network data quality rules, correlation logic, and entity resolution methods.
• Create reusable analytical models for RAN, Core, IP/MPLS, SD‑WAN, fixed, and cloud network KPIs.
• Support AIOps use cases such as alarm reduction, incident prioritisation, predictive maintenance, and automated root‑cause analysis.
• Work with OSS and inventory teams to align data models with TMF SID concepts and TMF Open API structures.
• Use BigQuery or equivalent analytics platforms to process large‑scale network data.
• Ensure models are explainable, measurable, governed, and suitable for operational decision‑making.

Skills

Python

Statistics

ML basics

Network KPI modelling

AIOps analytics

Graph analytics

BigQuery

LLM understanding

Data pipelines

Tools

BigQuery

TMF Open API

Graph APIs

Job description

Capgemini is seeking an AI Data Scientist to apply data science, statistics, ML, graph analytics, and KPI engineering to enable autonomous network intelligence. You will work with network telemetry, topology, inventory, and service data to develop analytical insights and predictive intelligence for autonomous network operations.

The role involves building models for anomaly detection, fault prediction, and proactive assurance, plus developing data pipelines and TMF‑aligned data models.