Lead Data Analyst

Airtel Digital; Gurugram District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Airtel is seeking a Lead Data Analyst/Senior Manager to drive data-backed decision making across sales, revenue, billing, and customer experience. You will own analytics projects end-to-end, mentor junior analysts, and collaborate with Engineering, Marketing, Product, and Customer Experience to translate data into actionable insights and AI-enabled improvements.

The role emphasizes ownership of deliverables, high-quality execution, and the development of scalable analytics solutions to optimize

Qualifications

• Bachelor’s degree in a related field such as Engineering, Data Science, Statistics or Business Analytics.
• 4–7 years of data analysis with end-to-end ownership and clear business impact.
• Strong understanding of business processes including acquisition cycles, customer experience and workforce management.

Responsibilities

• End-to-End analytics execution using AI/ML to solve business problems in sales, billing, payments and customer experience.
• Mentor junior analysts, share best practices and set high-quality execution standards.
• Collaborate with cross-functional teams to provide data-driven, actionable insights.
• Apply machine learning models and predictive analytics to improve decision-making and reporting.
• Break down complex problems into structured analyses and clearly communicate findings.

Skills

Data analysis

AI/ML

Mentorship

Cross-functional collaboration

Education

Bachelor’s degree in Engineering, Data Science, Statistics or Business Analytics

Job description

Lead Data Analyst/Senior Manager

Airtel is a leading telecom provider with over 400 million subscribers. As a data-driven organization, we process 2 trillion events daily and store 100 PB of data, enabling smarter business decisions. With growing data demands and evolving use cases, we need faster, scalable decision-making powered by analytics and AI.

About the role:

As a Lead Data Analyst at Airtel, you will play a pivotal role in driving data-backed decision-making by providing actionable insights across various business functions. You will work independently to analyze complex business data related to sales, revenue, customer experience, and financial operations (billing, payments, collections). You will also contribute to the development of AI-driven solutions that improve business performance and optimize processes.

In this role, you will take ownership of your deliverables and work directly with cross-functional teams, including Engineering, Marketing, Product, and Customer Experience, to ensure the successful execution of analytics initiatives. You will also be expected to set an example for high-quality execution, share best practices, and mentor junior analysts to build a strong analytics foundation within the team.

Key Responsibilities:

• End-to-End Analytics Execution: Take ownership of data analysis projects, leveraging AI/ML to solve business problems and drive results in sales, billing, payments, and customer experience.
• Mentorship & Best Practices: Lead by example in executing analytics tasks with high quality, sharing best practices, and mentoring junior analysts to build a strong analytics foundation.
• Collaboration: Work closely with cross-functional teams to provide data-driven insights that align with business objectives, ensuring actionable outcomes.
• AI & Data Insights: Apply machine learning models and predictive analytics to identify patterns, improve decision-making, and automate reporting.
• Problem Solving & Communication: Break down complex problems into structured analysis, and communicate insights clearly to the stakeholders.

Preferred Qualifications:

• Education: Bachelor’s degree in a related field (e.g., Engineering, Data Science, Statistics, Business Analytics)
• Experience: 4-7 years in data analysis, with demonstrated ownership of end-to-end deliverables with clear business impact
• Business Knowledge: Strong understanding of business processes, including acquisition cycles, customer experience, workforce management.
• Technical Expertise