Data Scientist

WE-PLUS PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

WE-PLUS PTE. LTD. in Singapore seeks a data scientist to translate portfolio data and customer behavior into actionable business insights. You will build executive dashboards, support strategic planning, and drive data-led decisions across product, marketing, and risk teams.

Your work will involve large-scale analytics, advanced modeling, and clear storytelling for senior stakeholders. The role emphasizes collaboration with clients and internal data teams in a fast-paced environment.

Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, CS, Math, Economics, Engineering or related quantitative field.
• More than 5 years of experience in advanced analytics, BI, or consulting analytics.
• Experience with large-scale datasets and deriving 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 with Gen AI tools/platforms; cloud analytics preferred.
• Strong business acumen and executive storytelling.
• Strategic thinking with stakeholder management.

Responsibilities

• Analyze large-scale datasets to identify opportunities for portfolio growth and profitability.
• Develop insights across cardholder lifecycle: acquisition, activation, spend, retention.
• Translate analytics into clear business recommendations for senior management.
• Produce senior management dashboards and strategic performance reports.
• Create executive-ready presentations on portfolio performance and trends.
• Establish KPIs and measurement frameworks for planning and reviews.
• Deliver insights influencing product strategy, marketing, loyalty, and portfolio decisions.
• Automate recurring reporting and create reusable analytical assets.
• Present findings to senior executives and decision-makers.

Skills

Python

SQL

Power BI

Tableau

Data analytics

Machine learning

Customer segmentation

Data storytelling

Executive communication

Gen AI tools

Education

Bachelor's degree

Master's degree

Tools

Excel

Job description

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.