We+ Asia
Data Analytics & Strategic Insights Analyst
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Singapore
Work mode:
Onsite
Published on:
25 September 2026
What they need
About the Role
We are seeking a highly analytical and commercially minded Data Scientist to work with an end client - a leading issuer bank in Singapore. The role will leverage our client's transaction data, issuer portfolio data, customer behavior data, and other relevant datasets to generate actionable insights, strategic recommendations, and executive-level reporting that support business decision-making.
This individual will serve as a trusted advisor to both our client and the end client leadership team, helping identify growth opportunities, improve portfolio performance, optimize customer engagement strategies, and drive measurable business outcomes through data-driven insights.
Key Responsibilities
Data Analytics & Strategic Insights
Analyze large-scale transaction datasets to identify opportunities for portfolio growth, revenue enhancement, customer engagement, and profitability improvement.
Develop actionable insights across the cardholder lifecycle including acquisition, activation, spend growth, retention, attrition prevention, and customer value management.
Perform deep-dive analysis on portfolio trends, customer behaviors, merchant spend patterns, and market opportunities, at market and group levels.
Translate complex analytics into clear business recommendations for senior management and executive stakeholders.
Executive Reporting & Decision Support
Produce senior management dashboards, business reviews, and strategic performance reports.
Develop executive-ready presentations highlighting portfolio performance, emerging trends, growth opportunities, and risk indicators.
Establish key performance indicators (KPIs) and performance measurement frameworks to support strategic planning and business reviews.
Deliver insights and recommendations that influence product strategy, customer acquisition, marketing investments, loyalty initiatives, and portfolio management decisions.
Data Visualization & Automation
Automate recurring reporting and analytical processes to improve efficiency and scalability.
Create reusable analytical assets, reporting templates, and insight-generation frameworks.
Facilitate discussions with senior business leaders to understand business challenges and define analytics priorities.
Present findings and recommendations to senior executives and decision-makers.
Qualifications Required
Bachelor's or master’s degree in data science, Statistics, Computer Science, Mathematics, Economics, Engineering, or a related quantitative discipline.
5+ years of experience in advanced analytics, data science, business intelligence, or consulting analytics.
Experience working with large-scale datasets and developing business insights.
Advanced proficiency in Python, SQL, and data analytics methodologies.
Strong statistical analysis and data visualization skills.
Experience developing executive-level presentations and reports.
Technical Skills
Python
SQL
Power BI / Tableau
Excel and advanced reporting tools
Statistical modeling and machine learning techniques
Data visualization and storytelling
Experience with machine learning, predictive modeling, and customer segmentation.
Experience on working with latest Gen AI tools/ platforms
Cloud analytics platforms (preferred)
Key Competencies
Strong business and commercial acumen
Executive communication and storytelling
Strategic thinking and problem solving
Stakeholder management and influencing skills
Strong ownership of client deliverables
Data-driven decision making
Attention to detail and analytical rigor
Ability to translate complex analysis into actionable business recommendations
Preferred
Experience within financial services, payments, retail banking, or credit card portfolios.
Familiarity with issuer portfolio analytics, customer lifecycle management, and cardholder behavior analysis.
Proven experience operating as an individual contributor, with the ability to independently lead analytical workstreams, structure problem statements, and deliver high quality outputs without day to day supervision
Experience collaborating with bank data teams or working within a bank environment is strongly preferred.
Experience working in a client-facing consulting environment.
Working knowledge of banking data, including product level datasets (cards, retail banking, deposits, loans), customer behavior data, transaction flows, risk and credit data, or other relevant
financial data structures.
- Knowledge of payments, merchant, or transaction data ecosystems.
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