Job Description:

• Own daily, weekly, and monthly order and GMV target tracking across cities, stores, and platforms.
• Build and maintain cohort retention models by acquisition channel, city, and user segment.
• Track order frequency, ARPU, and LTV by cohort; translate insights into actionable interventions.
• Lead weekly performance reviews and flag risks to monthly targets with root-cause analysis.
• Analyze app-level user journeys: install → signup → first order → repeat, including screen-level drop-off and feature adoption.
• Identify friction points in search, browse, cart, checkout, and payment flows.
• Translate diagnostics into concrete product change recommendations: UI changes, default settings, journey reordering, voucher logic, recommendation inputs.
• Partner with Product Managers on prioritization, A/B test design, and post-launch impact measurement.
• Identify gaps in event tracking and data coverage that limit growth analytics.
• Propose new BigQuery tables, columns, partitioning strategies, and event schemas.
• Partner with Data Engineering on data contracts; ensure every new product feature is instrumented before launch.
• Maintain a roadmap of data model improvements aligned with growth priorities.
• Manage and develop the team; run weekly 1:1s, quarterly performance reviews, and skill development planning.
• Build a culture of analytical rigor, ownership, and product thinking within the pod.

Skills & Qualifications:

• Bachelor’s degree in Business, Economics, Engineering, Computer Science, Statistics, or a related field; Master’s preferred.
• 5–7 years of total experience, with at least 3 years in analytics, growth, or product analytics roles.
• Strong SQL proficiency; BigQuery preferred, with experience writing complex queries using CTEs, window functions, and partitioned tables.
• Hands-on experience with at least one product analytics tool such as Mixpanel, Amplitude, GA4, or Firebase.
• Working knowledge of Python (pandas) and advanced Excel/Google Sheets.
• Solid understanding of unit economics, including GMV, AOV, CAC, LTV, payback, and contribution margin.
• Prior experience in q-commerce, food delivery, ride-hailing, e-commerce, or fintech.
• Experience working directly with Product Managers on PRDs and A/B test design.
• Exposure to subsidy, voucher, and promotions optimization in a marketplace or app-based business.
• Familiarity with fraud detection concepts.