Data Science (Banking)

Malaysia

Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.

ABOUT CAPCO

Capco is a global technology and business consultancy, focused on the financial services sector. We are passionate about helping our clients succeed in an ever-changing industry. You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.

ROLE DESCRIPTION

The Data Scientist leads analytical workstreams across end-to-end business portfolio optimisation initiatives, transforming large-scale transaction and customer data into actionable insights and data-driven strategies.

Leveraging advanced analytics and machine learning techniques, this role enables clients to make smarter decisions across the business lifecycle. The Data Scientist drives measurable impact through modelling, experimentation, and performance tracking—supporting payment volume growth, profitability improvement, and risk optimisation across client portfolios.

Key Responsibilities

• Lead analytics workstreams across the credit card portfolio lifecycle, including acquisition, activation, usage, retention, payment success, fraud, and credit risk

• Develop and deploy statistical models and machine learning solutions to identify opportunities for growth, efficiency, and risk mitigation

• Perform customer segmentation, lifecycle modelling, propensity modelling, and uplift analysis to inform portfolio strategies

• Design and evaluate test-and-learn frameworks, including A/B testing, control groups, and causal inference methodologies

• Analyse large-scale transaction, customer, and behavioural datasets (e.g., issuer and network data) to generate actionable insights

• Prepare and engineer datasets for predictive modelling, including parsing and aggregating structured and unstructured data

• Optimise and enhance code supporting critical business processes

• Design and develop dashboards using tools such as Tableau or Power BI

• Translate complex analytical findings into clear, actionable recommendations for business and client stakeholders

• Identify opportunities to automate repeatable analyses and build scalable analytical solutions

• Lead knowledge transfer to support implementation of analytics-driven business solutions

• Document analytical methodologies, code, and project outputs to ensure reproducibility and governance

• Collaborate closely with Product, Marketing, Risk, Fraud, and Technology teams to operationalise analytics-driven strategies

• Support executive-level storytelling through impactful presentations, dashboards, and performance tracking

• Contribute to capability building by developing best practices, reusable assets, and standardised methodologies

Qualifications

• Master’s degree or higher in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field

• 5–8+ years of experience in data science or advanced analytics, ideally within financial services or retail banking

• Proven experience in credit card portfolio analytics, customer lifecycle modelling, or marketing optimisation

• Strong expertise in statistical modelling techniques (e.g., regression, clustering, classification)

• Experience working with large datasets using tools such as SQL, Hive, Hadoop, Spark, Python, or cloud-based analytics platforms

• Solid foundation in statistical inference, experimental design, causal inference, and time series analysis

• Hands-on experience with both supervised and unsupervised machine learning techniques

• Exposure to fraud analytics, credit risk, authorisation, or payment success optimisation is preferred

• Demonstrated ability to translate analytical insights into business strategies and client recommendations

• Strong communication skills, with the ability to convey complex concepts to non-technical stakeholders

• Experience in consulting or client-facing analytics roles is highly advantageous

NEXT STEPS

If you’re looking forward to progressing your career with us, please do not hesitate to apply. We are looking forward to receiving your application.

To learn more about Capco and its people check out the website on www.capco.com