Data Analyst (Payment Operations)

Role Summary
The Data Analyst (Payment Operations) is responsible for analyzing payment operations data to identify trends, resolve operational issues, and drive continuous process improvement. This role transforms complex payment and financial data into meaningful insights that enhance service quality, operational efficiency, and business performance.

Key Responsibilities:

• Lead end-to-end data analysis by understanding operational processes and translating business needs into analytical insights.

• Conduct deep-dive Root Cause Analysis on payment failures, system discrepancies, and operational bottlenecks to provide solutions and prevent recurrence.

• Design and develop user-friendly dashboards and reports (e.g., Power BI, Looker, or similar tools) to monitor key performance indicators (KPIs) and provide real-time business visibility.

• Define and implement analytical frameworks to identify business trends, operational gaps, and opportunities for process improvement.

• Ensure data integrity and continuously improve data collection logic and reporting accuracy.

• Collaborate with cross-functional teams (e.g., IT, Product) to translate business requirements into technical or data solutions.

• Proactively identify opportunities to improve existing workflows and drive the transition from manual processes to more automated and digital data processes.

• Work independently to generate insights, recommend improvements, and support data-driven decision-making across teams.

Qualifications:

• Bachelor’s degree in Data Analytics, Computer Science, Statistics, Finance, or a related field.

• Minimum 3-4 years of hands-on experience in Data Analytics roles.

• Strong experience with data visualization tools (e.g., Power BI, Looker, Tableau) and advanced Excel skills including Macros or RPA.

• Strong analytical thinking with the ability to translate data into actionable insights and business recommendations.

• Experience working with financial services, payment systems, or subscription-model business is a plus.

• Knowledge of project management processes such as UAT and Go-live cycles is a plus

• Ability to work independently, manage multiple projects, and meet tight deadlines with strong attention to detail.

• Strong communication, presentation, and interpersonal skills; ability to clearly present data insights to both technical and non-technical stakeholders.

• Proactive in exploring and adopting Generative AI tools or machine learning frameworks to enhance data automation and analytics capabilities.

• Good command of English (both verbal and written) is a plus.