Product Data Analyst

As a Principal Data Analyst, you will define and drive the analytics strategy, ensuring customer-focused, data-backed decision-making. You will break down complex problems, create future-proof solutions, and execute them with high standards of quality. Your key stakeholders include Engineering, Business, Marketing, Customer Experience, and Product teams.

We are looking for a strategic thinker and AI-driven problem solver with a deep understanding of B2B business models—including sales funnels, delivery cycles, billing, payments, collections, and customer experience. You should have a strong foundation in AI and machine learning, including Generative AI applications in business intelligence, predictive analytics, and automation. You will work closely with teams across Airtel to embed AI-powered insights into business decisions and drive B2B performance optimization.

Key Responsibilities

Define Analytics & AI Vision & Strategy:

• Set the vision, define key business and product metrics, and align stakeholders
• Develop measurement frameworks, establish AI/ML-driven insights, and ensure data quality.
• Identify opportunities for AI-driven automation and predictive modelling.

Drive AI & Data-Backed Business Insights:

• Identify and decode patterns in sales, revenue, customer experience, and financial operations (billing, collections, payments) using AI-powered forecasting and anomaly detection.
• Apply machine learning models to improve lead-to-revenue conversion, optimize sales cycles, and reduce churn.
• Experiment with Generative AI tools to enhance analytics storytelling, automate reporting, and create personalized insights for stakeholders.

Own End-to-End AI & Analytics Execution:

• Work hands-on with data teams to define ML-driven hypotheses, run experiments, and measure impact.
• Ensure AI-driven analytics is embedded from day 0 in product and business initiatives.
• Identify key business problem statements, break them down into AI-powered analytics solutions, and drive clarity across functions.

Communicate AI-Driven Insights with Impact:

• Translate complex AI and machine learning insights into clear, compelling, and actionable stories for senior leadership.
• Evangelize AI and ML-driven decision-making, ensuring business and product teams harness AI’s full potential.

Cross-Functional Collaboration & AI Readiness:

• Work closely with sales, marketing, experience, product, and data teams to drive AI-powered analytics initiatives.
• Partner with engineering and data science teams to build scalable AI and ML solutions.
• Stay at the forefront of AI/ML advancements, evaluating LLMs, Generative AI, and predictive modelling frameworks for business intelligence.

Preferred Qualifications

Experience: 10+ years in analytics, with at least 4+ years leading a team of 10+ members in a senior role.

Business Knowledge:

• Strong understanding of B2B sales cycles, revenue models, customer journey mapping, pricing, billing, and collections.
• Deep knowledge of business KPIs, including lead conversion, order booked, revenue, churn, billing, collection and financial performance indicators.

AI & ML Expertise:

• Hands-on experience with AI/ML algorithms, Generative AI, and predictive analytics for business decision-making.
• Strong proficiency in Python, PySpark, TensorFlow, Scikit-Learn, or similar AI/ML tools.
• Experience deploying machine learning models for revenue forecasting, churn prediction, and anomaly detection.
• Ability to leverage LLMs (like GPT, Claude, or Gemini) to automate reporting, insights generation, and customer analytics.

Technical & Data Analytics Skills:

• Data Strategy & Governance: Ability to define frameworks, set standards, and ensure compliance with data regulations.
• Advanced Analytics: Proficiency in A/B testing, cohort analysis, MECE methodologies, and predictive modeling.
• Data Infrastructure: Understanding of ETL pipelines, data warehousing, and cloud-based AI analytics platforms.
• Data Visualization: Expertise in BI tools (Tableau, Power BI, Looker) to tell compelling stories.

Problem Solving & Storytelling:

• Ability to break down complex AI problems into structured analysis and change approach when needed.
• Strong storytelling skills, making AI insights accessible and actionable for business leaders.

Leadership & AI Evangelism:

• Track record of building and scaling AI-driven analytics teams.
• Proven ability to engage stakeholders at all levels, evangelizing AI-driven business transformation.