Join Capgemini and empower your career within a dynamic global community. We help leading Consumer Products and Retail Services organizations leverage technology for scalable, sustainable growth. Discover a workplace that values flexibility, fosters an inclusive culture, and provides continuous learning opportunities in emerging technologies like cloud and AI. At Capgemini Engineering, we are the world leader in engineering services, bringing together experts to help innovative companies unleash their potential across all industries.

As a global business and technology transformation partner, Capgemini accelerates dual transformations for organizations, addressing evolving customer and citizen needs. With a 55-year heritage and deep industry expertise, we are trusted to manage the full spectrum of business needs, from strategy and design to operations. Our 360,000 team members worldwide are driven by the purpose of unleashing human energy through technology for an inclusive and sustainable future. We are a responsible, diverse organization with market-leading capabilities in digital, cloud, and data.

Analyze telecom network data across RAN, Core, IP, Transport, SD-WAN, Cloud, OSS, and service domains. Develop robust KPI models for performance, quality, faults, customer impact, capacity, and resilience. Build advanced ML models for anomaly detection, fault prediction, root-cause analysis, and proactive assurance. Create efficient data pipelines for aggregation, cleansing, enrichment, and feature engineering. Support digital twin and graph analytics for topology, dependencies, service impact, and fault propagation. Develop frameworks for network data quality, correlation, and entity resolution. Enable critical AIOps use cases, including alarm reduction, incident prioritization, predictive maintenance, and RCA. Collaborate closely with AI/LLM teams, providing essential datasets, features, embeddings, and metadata for RAG and AI agents. Align network data models with industry-standard TMF SID/Open API specifications.

A minimum of 10 to 17 years of experience is required for this role.

Proficiency in Python, Statistics, and Machine Learning is essential.

Deep understanding of KPI & Feature Engineering is crucial.

Expertise in Network Performance Analytics, covering RAN, Core, IP, SD-WAN, and Transport domains.

Strong capabilities in Fault Analysis, Correlation, and Anomaly Detection.

Experience with AIOps & Predictive Analytics.

Skilled in Data Pipelines & Quality Management.

Familiarity with TMF SID/Open APIs.

Experience in Graph Analytics & Digital Twin Analytics.

Proficiency with BigQuery or equivalent platforms.

Knowledge of LLMs, RAG, and AI Agents is highly valued.