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AI Data Scientist - Autonomous Network
Am I a fit — voir ma compatibilitéCapgemini recrute un AI Data Scientist pour développer des modèles de machine learning, d’analyse statistique et de graph analytics appliqués aux réseaux télécoms autonomes. Le poste implique notamment la détection d’anomalies, l’analyse des incidents, l’ingénierie des KPI et la création de pipelines de données, avec Python, BigQuery et des données réseau. Basé au Royaume-Uni, ce rôle permanent suit un modèle hybride et nécessite un niveau de security clearance.
Repères sur Capgemini
- Domaine officiel
- capgemini.com
- Offres ouvertes
- 188
Détails de l’offre
La description complète publiée par Capgemini.
Your Role
This role focuses on applying data science, statistics, machine learning, graph analytics, and KPI engineering to enable autonomous network intelligence. The AI Data Scientist will work with network telemetry, alarms, performance counters, inventory data, topology data, trouble tickets, service data, and digital twin models to develop analytical insights and predictive intelligence for autonomous network operations.
Key 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.
Your Profile
Experience in data science, machine learning, 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.
Required Technical Skills
Python.Statistics and ML basics.Network KPI modelling.RAN, Core, IP, SD-WAN, and Transport KPI understanding.Fault analysis and anomaly detection.AIOps analytics.Data aggregation and data pipelines.KPI engineering and feature engineering.Inventory models.Fault correlation.
Tmf sid
understanding.BigQuery or equivalent analytics platform.Graph APIs and graph analytics.Digital twin analytics.LLM understanding. Preferred CertificationsGoogle Cloud Data Engineer or Machine Learning Engineer.Azure Data Scientist or AWS Machine Learning certification.Databricks, Snowflake, or equivalent data platform certification.TM Forum SID, Open API, or Autonomous Networks training. Nice-to-Have
Qualifications
- Experience : with telecom digital twin platforms.
- Experience : with vector databases, embeddings, semantic search, or RAG.
- Experience : with streaming data platforms such as Kafka, Pub/Sub, Flink, or Spark Streaming.
- Experience : supporting closed-loop automation, predictive assurance, or self-healing network use cases.
- Experience : working with OSS systems, inventory platforms, assurance systems, and ticketing data.
If you're excited about this role but don’t meet every requirement, we stillencourage you to apply, your unique experience could be just what we need.Make it real – what does it mean for you? Exposure to top global companies working withCapgemini (145 of the Fortune 500 companies)Open access to digital learning platformsActive employee networks promoting diversity, equity and inclusion like OutFront, CapAbility or Women@CapgeminiCapgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme.
As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:Declare they have a disability, and Meet the minimum essential criteria for the role.Please opt in during the application process.Capgemini. Make it real.Need to knowAll roles will require a level of security clearance
Bpss or
Security Clearance OR Developed Vetting. Location: This is a permanent role with Capgemini, offering a hybrid working model. The client is based in Newbury and occasional travel to the client site will be required.You can bring your whole self to work. At Capgemini building an inclusivefuture is part of everyday life and will be part of your working reality. We havebuilt a representative and welcoming environment, for everyone.About CapgeminiCapgemini is an AI-powered global business and technology transformation partner, delivering tangible business value.
We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion. Make it real | www.capgemini.com
Prérequis
- Strong knowledge of statistics, ML basics, feature engineering, and model evaluation
- Experience with network KPIs, alarms, telemetry, inventory, topology, or service assurance data
- BPSS OR Security Clearance OR Developed Vetting
Avantages mentionnés
- Open access to digital learning platforms
- Active employee networks promoting diversity, equity and inclusion
- hybrid working model