Principal Diagnostics Intelligence Lead (Telecom) - Diagnostics & Customer Experience Analytics

Role Purpose

Develop advanced diagnostics, predictive analytics and AI-driven insight capabilities that transform network, customer and transactional data into actionable intelligence.

The role will establish analytical products that identify customer experience issues, understand root causes, predict future service degradation and enable preventative intervention before customers are impacted or contact support.

Working across customer, network, transaction and diagnostics datasets, the successful candidate will help evolve Diagnostics capability from descriptive reporting towards predictive and preventative customer experience management.

Key Outcomes

The successful contractor will:

• Develop predictive models that identify customers at risk of service degradation.
• Create diagnostics analytics that explain why customer issues occur.
• Identify emerging trends, recurring faults and systemic customer experience drivers.
• Build AI-enabled capabilities to automate insight generation and root cause analysis.
• Develop self-service diagnostic tools and dashboards for operational teams.
• Correlate customer experience, network performance and transactional behaviour.
• Establish early warning indicators for customer-impacting issues.
• Enable proactive and preventative customer interventions before support contact is required.
• Reduce time to identify, diagnose and resolve customer issues.
• Build reusable analytical assets that accelerate future Diagnostics and AI initiatives.

Essential Experience

Data Science & Predictive Analytics

• Advanced Python development.
• Machine Learning and predictive modelling.
• Statistical analysis and pattern recognition.
• Time-series analysis and forecasting.
• Anomaly detection and behavioural analytics.
• AI and automation within analytical environments.

Mobile Network Analytics

• Mobile telecommunications analytics.
• RAN performance analysis.
• Customer experience analytics.
• User Plane analytics.
• Control Plane analytics.
• Transaction analytics.
• Service assurance and diagnostics analytics.
• Network event correlation and root cause analysis.
• Large-scale mobile network datasets.

Customer Experience Analytics

• Customer-level analytics and segmentation.
• Network-to-customer impact modelling.
• Behavioural analytics.
• Customer journey analytics.
• Identification of customer experience drivers and trends.
• Translating analytical findings into operational actions.

Technology

• Python.
• SQL.
• Snowflake.
• GCP / BigQuery.
• Dashboard and self-service analytics development.
• Modern AI and Machine Learning toolsets.

Highly Desirable

• Experience within Vodafone, Three, EE, O2 or other mobile operators.
• Experience working with network diagnostics platforms.
• Customer Experience Management (CEM) platforms.
• GenAI and LLM-based analytical solutions.
• Decision Intelligence and automated recommendations.
• Real-time analytics environments.