Flipkart - Manager - Central Last Mile - Flipkart Minutes

Description:

Role Summary: This is a high-impact, analytical role responsible for the financial modeling and cost-efficiency of our Pan-India last-mile operations. This position will own the analytical frameworks for rider payouts (rate cards and incentives) and will be the key analytical partner in auditing manpower supply plans. This role is critical for driving down our Cost Per Order (CPO) through data-driven insights.

Key Responsibilities:

- Financial & Payout Modeling: Design, build, and maintain complex financial models for all rider rate cards (per-trip, per-km, per-minute). Simulate the Cost Per Order (CPO) impact of all proposed rate card changes and provide clear recommendations.

- Incentive & ROI Analysis: Conduct robust ROI analysis on all incentive schemes (e.g., surge, festive bonuses). Deliver post-analysis reports on incentive effectiveness to guide future spending.

- Supply Plan Auditing: Perform a Cost & Efficiency Audit on weekly manpower plans submitted by the Supply team. Analyze the CPO and utilization impact of these plans, identifying risks of over-staffing or inefficiency.

- Deep-Dive & Zonal Analysis: Conduct deep-dive analytics to identify the root cause of cost variances between different zones or cities. Continuously benchmark payouts against competitors to ensure we remain cost-competitive.

Required Qualifications & Skills:

- Bachelor's degree in Engineering, Economics, Finance, Statistics, or a related quantitative field.

- 2-4 years of experience in a highly analytical role (e.g., FP&A, Business Analyst, Data Analyst, Operations Analyst).

- Advanced Excel: Proven mastery of financial modeling and building complex models from scratch.

- Strong SQL/Python: The ability to independently query, join, and manipulate large, complex datasets.

- Data Visualization: Experience with data visualization tools (e.g., Tableau, Power BI) to build clear and actionable reports.

- Analytical Mindset: Strong analytical, problem-solving, and detail-oriented mindset with the ability to find the root cause of a problem.

- Communication: Ability to communicate complex findings clearly and concisely.

- Familiarity with Python (Pandas) for data analysis is a strong plus.

- Experience in a high-growth, high-volume industry (e.g., e-commerce, logistics, ride-hailing) is preferred.