Uber
Website:
uber.com
Job details:
About The Role
As a part of the Economic Performance team, you will drive our partnership with SME teams on risk/fraud/payments ecosystem in APAC. You will sit at the intersection of data and operations, ensuring our processes are robust, our metrics are accurately reported & optimized and we're making the most of new opportunities in the commerce space. Your role is critical in identifying financial leakages, managing live incidents, and providing the data-driven insights necessary to scale our cash and payment products safely.
---- What the Candidate Will Do ----
- 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.
- 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.
- 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.
- 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.
- Payments & Cash Analytics: Power the initiatives that improve our unit economics. Analyze payment costs, success rates, and user behavior to optimize our cash-in/cash-out products.
- Process Optimization: Identify manual gaps in current risk/ops workflows and design data-driven solutions to automate or streamline them.
Basic Qualifications
- Experience: ~4 years of experience in an analytical role, preferably within FinTech, Payments, or Risk teams.
- Technical Proficiency: Advanced SQL is a must. Proficiency in data visualization tools (Tableau, Looker, or PowerBI) and Excel. Experience with Python/R for data analysis is a plus.
- Communication: Ability to distill complex analytical findings into crisp, actionable insights for operational stakeholders and leadership.
- Education: A Bachelor's or Master's degree in a quantitative field (Engineering, Economics, Math, or Finance).
Preferred Qualifications
- Problem Solving: A high degree of mental agility. You should be comfortable navigating through ambiguity and making data-backed decisions under pressure (especially during incidents).
- Operational Mindset: You don't just look at data; you understand the human and systemic processes that generate it. You are passionate about execution.
- Crisis Management: Ability to manage high-pressure situations and exercise strong judgment and clear communication
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