Data Scientist

⇒ Role Summary

We are seeking a highly analytical and commercially minded Data Scientist to work with our client - a leading issuer bank in Singapore. The role will leverage 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 Client’s and the bank's leadership team, helping identify growth opportunities, improve portfolio performance, optimize customer engagement strategies, and drive measurable business outcomes through data-driven insights.

⇒ Main Responsibilities

Data Analytics & Strategic Insights

• Analyze large-scale Client’s 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 & Experience

• Bachelor's or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or a related quantitative discipline.
• More than 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).
• 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.
• 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.