Data Analyst (Banking / Contract)

PERSOL Singapore; Singapore; Sur place; SGD 140 000 - 220 000; Plein temps

Résumé du poste

PERSOL Singapore is seeking a highly analytical Data Scientist to work with a leading issuer bank in Singapore. You will analyze large-scale Visa transaction data to uncover portfolio growth, revenue enhancement, and profitability opportunities, and deliver executive-ready insights for strategic decisions.

Responsibilities include building dashboards, presenting findings to senior leaders, and automating recurring reporting while leveraging GenAI and cloud analytics platforms.

Qualifications

• Advanced analytics and data science experience in finance or consulting analytics.
• Proficiency with large-scale datasets and deriving business insights.
• Strong Python, SQL, and data analytics methodologies.
• Experience with machine learning, predictive modeling, and customer segmentation.
• Experience with GenAI tools and cloud analytics platforms.

Responsabilités

• Analyze large-scale Visa transaction datasets to identify opportunities for portfolio growth, revenue enhancement, customer engagement, and profitability improvement.
• Develop executive-ready dashboards, business reviews, and strategic performance reports.
• Translate complex analytics into clear business recommendations for senior management and executive stakeholders.
• Establish KPIs and analytics frameworks to support strategic planning and governance.

Connaissances

Statistical analysis

Data visualization

Customer segmentation

Executive storytelling

Formation

Bachelor's or Master's degree in Data Science or related quantitative discipline

Outils

Python

SQL

GenAI tools

Cloud analytics platforms

Description du poste

About the Role

We are seeking a highly analytical and commercially minded Data Scientist to work with our client, a leading issuer bank in Singapore.

Data Analytics & Strategic Insights

• Analyze large-scale Visa 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.
• Experience with machine learning, predictive modeling, and customer segmentation.
• Experience working with the latest GenAI tools and platforms.
• Cloud analytics platforms (preferred).