Senior Officer (Data Analyst – Consumer Banking Department)

Duties and Responsibilities

• Analyze large datasets related to credit/debit/prepaid card usage, POS/e-commerce transactions, and digital wallet payments.
• Create dashboards and reports to track KPIs such as spend behavior, approval rates, decline reasons, fraud metrics, interchange revenue, loyalty  points, and campaign performance.
• Support product and campaign teams with segmentation, targeting, and post-campaign performance analysis.
• Monitor transaction patterns to identify anomalies, fraud trends, or opportunities to improve authorization rates.
• Collaborate with Risk and Compliance to support regulatory reporting (e.g., AML transaction monitoring, suspicious activity).
• Work closely with IT/Data Engineering to improve data extraction, cleaning, and structuring from CMS, switch, and third-party systems.
• Translate business questions into analytical models and queries, providing insights to support decision-making.
• Participate in the development and enhancement of data models, customer scoring, and predictive analytics (e.g., churn risk, credit limit optimization, propensity models).
• Present key insights and trends to senior management and product teams.

Education & Experience:

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Finance, or a related field.
• Have 3+ years of experience as a Data Analyst or Business Analyst, preferably in banking, fintech, or payment services.

Technical Skills:

• Proficiency in SQL, Excel, and data visualization tools like Power BI, Tableau, or Looker.
• Experience with Python, R, or other scripting languages for data processing is a plus.
• Familiarity with card transaction data, ISO 8583 message formats, and CMS/Switch systems is advantageous.

Soft Skills:

• Strong analytical mindset with attention to detail.
• Excellent communication skills to explain technical findings to non-technical stakeholders.
• Ability to handle multiple tasks and work under tight deadlines.

 Preferred Qualifications

• Knowledge of Visa, Mastercard, or UnionPay reporting tools (e.g., VROL, Visa Analytics Platform).
• Experience in working with fraud analytics, loyalty data, or merchant acquiring metrics.