Business Analyst, IES CFX & Prime

Our vision for Prime is to build India’s largest subscription program that is loved by its members, delivers disproportionate value and drives growth of India business. In order to achieve this mission, we are on a multi-year journey to re-imagine Prime program and build a program to meets needs of large diverse customer base in India. Our team is responsible for all aspects of the prime program including customer lifecycle management, plan constructs, trial strategies, pricing, program branding, Prime benefits, member spends and Prime PnL. To this end, we are a multidisciplinary team including product managements, marketing, business development, engineering and analytics. We are a team of builders who love to work backwards from customer, build empathy for their needs and invent products and services that will enrich their lives.

The Prime team is looking for a Business Analyst responsible for building analytics solutions and generating Prime-related insights for India and other emerging marketplaces. The ideal candidate will be skilled at building scalable, self-service analytics infrastructure, have experience creating analytical datasets and reports, and be naturally curious — someone who proactively seeks out data to understand business use cases and their impact on Prime. This candidate will be part of the core Prime Analytics team, responsible for providing analytics support and insight-driven solutions for the Prime business.

Key job responsibilities

Key Responsibilities

Understand the key drivers, impacts, and influences on the Prime program, particularly in member acquisition and growth. Analyze program impact and partner with stakeholders to define and track key performance indicators (KPIs). Translate data into actionable insights that inform stakeholder decision-making. Automate weekly business metric reporting and identify opportunities to scale ad-hoc analyses through automation. Perform complex data analysis — including root cause deep dives, correlations, regressions, simulations, and optimization — to identify opportunities and reduce process gaps. Build and maintain scalable data infrastructure and implement maintenance strategies for internal datasets to support swift analysis and answer critical business questions.