AI Data Scientist – Autonomous Network Intelligence

Capgemini; United Kingdom; Hybride; GBP 75 000 - 110 000; Plein temps

Avantages offerts par ce poste

Hybrid work model

Disability Confident Employer

Résumé du poste

Capgemini is seeking an AI Data Scientist to apply data science, ML, and graph analytics to autonomous network operations. You will work with telemetry, topology, and service data to build KPI models, anomaly detection, and predictive analytics.

Ideal candidates have strong Python, statistics, and BigQuery skills, plus experience with telecom domains such as RAN/Core/IP/MPLS/SD-WAN. Hybrid work and security clearance are part of the role.

Qualifications

• Experience in data science, telecom analytics, network performance analytics, or AIOps analytics.
• Strong Python skills for data analysis, modelling, and automation.
• Strong knowledge of statistics, ML basics, feature engineering, and model evaluation.
• Experience working 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.
• Experience developing anomaly detection, fault analysis, predictive analytics, or KPI models.
• Experience with data aggregation, cleansing, enrichment, and data quality assessment.
• Experience with graph analytics, entity relationship mapping, or knowledge graph concepts.
• Understanding of LLMs and how structured data can support AI agents and RAG systems.
• Experience with BigQuery or similar data warehouse/analytics platforms.

Responsabilités

• 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.
• Collaborate 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.

Connaissances

Python

Statistics basics

ML fundamentals

Network KPI modelling

AIOps analytics

Data pipelines

Graph analytics

LLM / RAG concepts

BigQuery

Telecom analytics

Outils

BigQuery

Description du poste

Capgemini is seeking an AI Data Scientist to apply data science, ML, and graph analytics to autonomous network operations. You will work with telemetry, topology, and service data to build KPI models, anomaly detection, and predictive analytics.

Ideal candidates have strong Python, statistics, and BigQuery skills, plus experience with telecom domains such as RAN/Core/IP/MPLS/SD-WAN. Hybrid work and security clearance are part of the role.