Data Analytics Specialist (Cards) - 12 months
Role Overview
Data Analytics Specialist supporting a leading banking project in Saudi Arabia.
The role focuses on credit and debit card products and cardholder lifecycle analytics.
Key Skills for This Role
Full Job Posting
Role overview
Data Analytics Specialist supporting a leading banking project in Saudi Arabia.
The role focuses on credit and debit card products and cardholder lifecycle analytics.
Key requirements
- 7+ years of experience in data analytics, data science, or related fields.
- Strong banking experience supporting credit and debit card products.
- Experience with cardholder lifecycle use cases from acquisition and cross-sell through retention, portfolio growth, profitability, and campaign design.
- Expertise in data analytics, predictive modeling, and data science; proficiency in Python, SQL, and SAS.
- Experience in card portfolio analytics, transaction analysis, customer segmentation, fraud detection, credit risk, or related banking analytics functions.
- Experience developing predictive models, customer behavior insights, and data-driven recommendations; ability to make complex data actionable for business stakeholders.
- Immediate availability requested.
Preferred qualifications
- Credit card transaction analytics, risk scoring, churn prediction, and portfolio performance reporting experience are preferred.
- Analytical and problem-solving skills are preferred.
- Power BI or Tableau experience is preferred.
- Currently being based in Saudi Arabia is preferred.
Responsibilities
- Analyze large-scale banking and card transaction datasets to identify trends, opportunities, and risks.
- Develop predictive models for business growth, customer retention, and risk management.
- Perform customer segmentation and behavioral analytics.
- Create dashboards and reports for business and product decision-making.
- Collaborate with stakeholders to define KPIs and deliver actionable insights.
- Support credit and debit card product teams with advanced analytics and data-driven recommendations.
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