1. Payment & Performance Evaluation (30%)
- Manage and allocate operational budgets (driver incentives, support programs, etc.) to ensure alignment with business objectives across different phases.
- Optimize operational costs through policy experimentation initiatives such as A/B testing, canary launches, and pilot programs by region or user segment.
- Provide data-driven recommendations to support operational and policy-related decision-making.
- Monitor and evaluate the effectiveness of operational policies and performance initiatives to ensure budget efficiency and business impact.
2. Reporting, Data Analysis & Documentation (30%)
- Act as the focal point for gathering business requirements and developing data systems (Data Mart, dashboards, reporting tools, etc.) to support operational monitoring and improvement initiatives.
- Deliver timely insights, analyses, and recommendations to stakeholders for accurate and effective decision-making.
- Establish, maintain, and standardize the team's documentation and knowledge management system to ensure continuity and scalability.
- Ensure reporting systems and data infrastructure operate accurately, efficiently, and meet defined service standards.
3. Technology Application & Project Development (20%)
- Lead the adoption and implementation of AI tools, automation solutions, and operational technologies to improve team productivity and efficiency.
- Initiate or participate in internal and cross-functional projects aimed at enhancing operational quality and business performance.
- Promote the application of AI and automation tools in the team's day-to-day operations.
- Ensure assigned projects are executed effectively and delivered according to plan.
4. Team Management & Development (20%)
- Manage team performance and support the professional development of team members.
- Build a motivated, engaged, and high-performing team environment.
- Ensure team members are equipped with the required capabilities and resources to fulfill their assigned responsibilities effectively.
Requirements
- Bachelor's degree in Data Analytics, Information Systems, Statistics, Economics, or related fields.
- Minimum of 3 years of experience in data analysis and reporting system development; prior experience managing small teams (4+ members) is preferred.
- Proficient in SQL, AI tools, and analytics platforms such as BigQuery, Metabase, Google Sheets, Python, or R.
- Hands-on experience working with Data Warehouses, Data Marts, and ETL processes.
- Strong understanding of A/B testing methodologies, causal inference, and performance evaluation models.
- Ability to present and visualize data clearly and effectively for different stakeholders.
- Strong documentation, knowledge-sharing, and process communication skills.
- Systematic thinking mindset with strong attention to detail and continuous improvement orientation.
- Proactive, collaborative, and capable of managing multiple cross-functional projects simultaneously.
- English proficiency is a plus.
