Sr Lead Data Analyst

Airtel Digital; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Airtel is seeking a Sr Lead Data Analyst to drive data-backed decisions across sales, billing, payments, and customer experience. You will own deliverables and work directly with cross-functional teams, including Engineering, Marketing, Product, and Customer Experience, to ensure successful analytics initiatives.

The role emphasizes mentorship, high-quality execution, and applying AI/ML techniques to improve business performance and automate reporting.

Qualifications

• 8–10 years in data analysis with end-to-end ownership.
• Strong business knowledge in analytics for sales, revenue, and CX.
• Proficiency in SQL, Python, and visualization tools.
• Experience with AI/ML techniques and predictive analytics.

Responsibilities

• Lead end-to-end analytics projects using AI/ML to drive sales, billing, payments, and CX.
• Mentor junior analysts and promote best practices.
• Collaborate with cross-functional teams to translate data into actionable insights.
• Develop and implement predictive models and automated reporting.
• Communicate findings to stakeholders clearly.

Skills

SQL

Python

Pyspark

Tableau

Power BI

Excel

ETL pipelines

Data warehousing

Cloud-based AI analytics

A/B testing

Cohort analysis

MECE methodologies

Predictive modelling

Generative AI tools

Education

Bachelor's degree in Engineering, Data Science, Statistics or related field

Job description

About the role:

As a Sr .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: 8-10 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: Proficiency in data analysis and visualization tools (e.g., SQL, Python, Pyspark, Tableau, Power BI, Excel) Understanding of ETL pipelines, data warehousing, and cloud-based AI analytics platforms Proficiency in A/B testing, cohort analysis, MECE methodologies, and predictive modelling

AI/ML Knowledge: Solid foundation in applying AI/ML techniques (Regression, Random Forest, Boosting techniques) to business data, including predictive analytics and anomaly detection. Basic experience with machine learning tools and frameworks such as Python, Scikit-Learn, or similar. Familiarity with Generative AI tools and their application in business intelligence and reporting is a plus.

Mentorship & Leadership: Proven ability to mentor junior analysts and foster a collaborative, learning-oriented team environment.