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.