Data Scientist

Job Responsibilities

As a Data Scientist, you will lead and support credit data analytics, credit score modelling and machine learning initiatives to strengthen credit risk management and support data-driven business decisions.

Your key responsibilities include:

• Lead credit data analytics and modelling initiatives by analysing customer, credit and collection data to identify trends, patterns, risks and opportunities across the credit portfolio.
• Develop, implement and monitor credit scoring models and predictive models to support credit assessment, risk management, collection strategies and overall portfolio performance.
• Apply data science and machine learning techniques to solve business and credit-related problems, including data mining, feature engineering, model development, validation and performance monitoring.
• Translate complex data and analytical findings into actionable business insights and recommendations for management, credit policies and business strategies.
• Develop and maintain data analytics pipelines and solutions, ensuring data quality, accuracy and reliability throughout the data lifecycle.
• Support machine learning model deployment and maintenance (MLOps), including model implementation, monitoring, performance tracking and continuous improvement.
• Analyse consumer and market behaviour and conduct competitor and market benchmarking to identify emerging trends and potential business or credit risks.
• Collaborate with Credit, Risk, IT, Data, Business and other relevant stakeholders to understand business requirements and develop practical, data-driven solutions.
• Lead digital transformation and automation initiatives involving credit analytics, machine learning, predictive modelling and digital solutions.
• Monitor portfolio and model performance and provide regular analysis and reporting to identify areas requiring corrective action or improvement.
• Lead, coach and develop team members, providing technical guidance, knowledge sharing and mentoring to strengthen the team's analytical and modelling capabilities.
• Ensure analytical projects are delivered accurately and within agreed timelines, while maintaining appropriate documentation, governance and quality standards.

Job Requirements

• Bachelor's Degree or higher in Data Science, Statistics, Mathematics, Computer Science, Economics, Actuarial Science, Finance, or other relevant disciplines.
• Minimum 8 years of relevant experience in Data Science, Credit Risk Analytics, Credit Modelling, Predictive Modelling or related fields.
• Candidates with experience in banking, financial institutions, credit card, consumer finance or other financial services environments will have an added advantage.
• Minimum 3 years of experience in a supervisory or leadership capacity, with demonstrated experience in managing, mentoring or developing team members.
• Strong experience in analysing credit portfolio, customer behaviour, credit risk or collection data and translating analytical findings into business recommendations.

Technical Skills

• Strong proficiency in SQL for data extraction, manipulation and analysis.
• Proficiency in Python or R for data analysis, statistical modelling and machine learning.
• Practical knowledge of machine learning algorithms, predictive modelling and data mining techniques.
• Good understanding of feature engineering, model development, model validation and performance monitoring.
• Knowledge of credit scoring / scorecard development and validation techniques.
• Understanding of MLOps, model deployment and model maintenance will be an advantage.
• Experience with AWS Cloud Services is preferred; experience with other cloud platforms will also be considered.
• Experience with data visualisation and business intelligence tools such as Tableau, Power BI or similar tools is an advantage.
• Good understanding of credit operations, credit processes and credit policies.