Sr. Business Operations Manager, Apac

Uber Uber · Consumer · Gurgaon, India · Operations

This role focuses on the operational aspects of risk, fraud, and payments within Uber's APAC operations. The candidate will partner with Risk & Fraud ops, translate analytics into actionable insights, track key performance indicators (KPIs), handle incidents, and optimize processes. The role requires strong analytical skills, advanced SQL, proficiency in data visualization tools, and the ability to make data-backed decisions under pressure. It is not directly involved in building or researching AI/ML models but uses data analysis to support business operations in a regulated domain.

What you'd actually do

  1. Partner with Risk & Fraud ops: Monitor real-time fraud patterns and risk metrics. Identify anomalies and work closely with the Risk Ops team to implement immediate mitigation strategies.
  2. Translate Analytics to Imperatives: Act as the primary analytical bridge between Economic Performance and the APAC Ops/Risk Ops teams. Translate operational challenges into data problems and vice versa.
  3. Metric Tracking & Reporting: Own the source of truth for Commerce KPIs. Build and maintain automated dashboards that track loss rates, false positives, and payment success rates.
  4. Incident Handling: Lead the analytical response during risk or payment incidents. Perform rapid root-cause analysis (RCA) and coordinate with cross-functional teams to resolve issues and prevent recurrence.
  5. Payments & Cash Analytics: Power the initiatives that improve our unit economics. Analyze payment costs, success rates, and user behaviour to optimize our cash-in/cash-out products.

Skills

Required

  • Advanced SQL
  • Data visualization tools (Tableau, Looker, or Power BI)
  • Excel
  • Analytical role experience
  • FinTech, Payments, or Risk teams experience
  • Bachelor’s or Master’s degree in a quantitative field (Engineering, Economics, Math, or Finance)
  • Ability to distill complex analytical findings into crisp, actionable insights
  • Comfort navigating through ambiguity
  • Making data-backed decisions under pressure
  • Understanding of human and systemic processes that generate data
  • Ability to manage high-pressure situations
  • Strong judgment
  • Clear communication

Nice to have

  • Python/R for data analysis

What the JD emphasized

  • Advanced SQL is a must