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Risk Analytics - Telecom and Data Analytics - Manager

Location:  Gurgaon
Other locations:  Anywhere in Country
Salary: Competitive
Date:  May 26, 2026

Job description

Requisition ID:  1710549

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We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. 

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Telecom & Data Analytics  - Manager

 

 

Role Overview

 

We are seeking an experienced Data Analytics Manager with Telecom domain expertise to lead analytics-driven decision-making, automation initiatives, and revenue optimization strategies. The role combines deep telecom business understanding with strong technical expertise in SQL, Power BI, and Python-based automation.

 

The candidate will drive data-led transformation across billing, revenue assurance, fraud detection, and operational efficiency, while managing a team of analysts and automation engineers.

 

 

Key Responsibilities

 

Telecom Domain Leadership

  • Lead analytics initiatives across Revenue Assurance, Billing, Fraud Management, and Leakage Detection
  • Identify revenue leakages, billing gaps, and operational inefficiencies using data insights
  • Partner with business stakeholders to define KPIs and performance dashboards
  • Drive process optimization and automation opportunities across telecom operations
  • Ensure alignment with telecom regulatory, billing, and audit requirements
  • Provide domain consulting support for BSS/OSS, mediation, interconnect (operator to operator billing) and billing systems

 

Data Analytics & Visualization (Power BI, SQL)

  • Design and deliver interactive Power BI dashboards for executive and operational reporting
  • Develop complex SQL queries and data models for telecom datasets
  • Perform data validation, reconciliation, and root cause analysis
  • Enable self-service analytics capabilities across business teams
  • Standardize reporting frameworks and ensure data governance best practices

 

Automation & Advanced Analytics (Python)

  • Drive end-to-end automation use cases using Python (ETL, reconciliation, anomaly detection)
  • Build scalable automation frameworks for:
    • Revenue leakage detection
    • Fraud analytics
    • Data quality monitoring
  • Integrate Python solutions with existing data platforms and workflows
  • Promote AI/ML-based use cases (predictive analytics, anomaly detection)

 

Team Management & Delivery

  • Lead and mentor a team of data analysts and automation engineers
  • Define roadmap for analytics maturity and automation adoption
  • Ensure timely delivery of analytics solutions and business insights
  • Conduct trainings on SQL, Power BI, and Python for team capability building
  • Collaborate with cross-functional teams (IT, Finance, Operations)

 

Stakeholder & Strategic Engagement

  • Work with senior leadership to translate business needs into analytics solutions
  • Present insights and recommendations to stakeholders
  • Drive data-driven culture within telecom operations
  • Support transformation initiatives and digital modernization programs

 

 

Required Skills & Qualifications

 

  • Domain Expertise (Mandatory)
  • 8–15+ years in Telecom / Data Analytics / Revenue Assurance / Fraud Management
  • Strong understanding of:
  • Telecom billing systems
  • Revenue leakage detection
  • Mediation and usage data flows
  • Telecom KPIs and metrics

 

 

Technical Skills (Mandatory)

 

  • SQL (Advanced) – data extraction, joins, optimization
  • Power BI (Advanced) – dashboards, DAX, data modeling
  • Python (Intermediate/Advanced) – automation, data processing

 

 

Preferred Skills

 

Experience with:

 

  • Data Analytics and Data Warehousing concepts
  • Python based automation and ETL Operations
  • Visualization and reporting experience using Power BI/Tableau/Splunk dashboards.
  • Knowledge of Machine Learning concepts (nice to have)
  • Alteryx or Power Automate (nice to have)

 

 

Key Deliverables / Success Metrics

 

  • Reduction in revenue leakage and fraud exposure
  • Increased automation coverage across telecom processes
  • Dashboard adoption and data-driven decision making
  • Improved operational efficiency and turnaround time
  • Team capability uplift and skill development

 

 

Leadership Competencies

 

  • Strong analytical thinking and problem-solving skills
  • Excellent stakeholder management and communication
  • Ability to translate business problems into technical solutions
  • Strategic thinking with execution focus
  • Team leadership and mentoring capability

 

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