Data Analytics Specialist (Banking, Card& Loyalty)

We seek a Senior Data Analyst with substantial experience in banking, loyalty programs, and card usage analytics. You will take ownership of data analysis across loyalty and cross-sell initiatives, provide business insights, and collaborate with product, CRM, and marketing teams to drive impactful decisions through data.

You will play a key role in uncovering customer behavior patterns, optimizing campaign performance, and identifying revenue growth opportunities across digital banking services.

Key Responsibilities

• Analyze card usage, transaction patterns, earn/burn behaviors, and loyalty program performance.
• Define, calculate, and monitor key metrics: retention, engagement, CLTV, churn, and campaign performance.
• Support and evaluate cross-sell, up-sell, and reactivation campaigns using quantitative methods.
• Collaborate with cross-functional teams (Product, Marketing, CRM) to design and evaluate A/B tests, segment analysis, and personalized targeting.
• Build and maintain BI dashboards and self-service tools for stakeholders.
• Ensure data consistency, availability, and business logic alignment across analytics assets.
• Mentor junior analysts (if any) and contribute to best practices in data analysis.

• 3+ years of experience in Data Analytics, preferably in Banking, Loyalty, or Fintech.
• Strong SQL skills and experience working with modern data warehouses (e.g., Snowflake, S3, Redshift).
• Proven experience working with BI tools such as Metabase, Power BI
• Deep understanding of customer behavior metrics and analytics frameworks.
• Strong data visualization and storytelling skills.
• Excellent communication skills – able to work with both technical and non-technical stakeholders.
• Business acumen in card/lending products, customer lifecycle, and digital banking journeys.
  
  

Nice to Have

• Hands-on experience with Python or R for data analysis or automation.
• Familiarity with CEP platforms (e.g., Moengage), CDPs, or marketing automation tools.
• Experience in campaign attribution modeling, uplift modeling, or predictive segmentation.
• Leadership or mentoring experience is a plus.

• Data-first culture with support from Product and Engineering teams.
• Access to rich datasets across banking and loyalty platforms.
• Flexible working environment and learning opportunities.
• Competitive salary package (Base salary and performance bonuses).
• Probation period salary is 100% of the official salary.
• Comprehensive health and accident insurance.
• 15 days of annual leave.
• Provision of work equipment (Macbook/ Laptop, mouse, monitor, etc.).
• A creative and modern working environment.