Senior / Principal Data Scientist

SUMMARY OF RESPONSIBILITIES 

• Data Science & Engineering
• Financial Crime & Fraud 
• Projects & Others

KEY AREAS OF RESPONSIBILITIES

DATA SCIENCE & ENGINEERING

• Pursue ecosystem fraud mitigation and broader data initiatives and use cases that drive innovation across the financial ecosystem
• Explore, develop, and enhance machine learning models and other algorithms used for ecosystem fraud detection (e.g., National Fraud Portal, identity/ account/ transaction profiling & scoring, analysis & discovery of new Modus Operandi, deeper insights on fraud networks, etc.)
• Explore newer generation technologies to continue to uplift functional capabilities across the division and organisation 
• Identify, develop, maintain, support and continuously enhance data pipelines and infrastructure to support organization-wide data science & analytics initiatives, and to ensure data is accessible, secure and usable
• Collaborate with engineering teams to deploy and monitor models in production
• Drive, deliver and support cross-functional and cross-divisional data science projects as well as broader business-related business intelligence use cases that support delivering customer insights, product innovation, and operational excellence
• Create dashboards, visualizations, and reports to communicate findings to stakeholders

FINANCIAL CRIME & FRAUD

• Support the fraud team in performing data analysis and explore any other fraud mitigation measures and strategies to improve collective ecosystem fraud prevention capabilities
• Support the fraud team in developing, maintaining and enhancing financial crime & fraud solutions operated by PayNet (e.g., National Fraud Portal, Fraud Kill Chain, etc.)
• Support industry/ ecosystem engagements (e.g., industry data workshops, industry POCs with banks, e-wallets, regulators, etc.)

PROJECTS & OTHERS

• Drive/ support cross-divisional, cross-functional or greenfield data projects 
• Any other related area that is assigned by the Head, Fraud & Projects and Director of Risk & Compliance.

QUALIFICATIONS

1. Minimum Qualifications 

• Degree in Data Science, Information Technology, Business Administration or other related discipline.
• More than 5 years relevant experiences in data science and/ or engineering.

2. Technical Qualifications

• Programming Skills – Well versed in various data programming languages e.g., Python, SQL, etc.
• Machine Learning Libraries – Experienced in machine learning libraries e.g., scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
• Big data – Experienced in big data technologies e.g., Hadoop, Spark, etc.
• Cloud – Experienced with AWS stack, including S3, Lambda, Glue, SageMaker, and Redshift
• Graph Database – Worked with graph databases e.g., Neo4j, AWS Neptune, etc.
• Data analytics – Demonstrates ability to derive meaningful insights from data, with the ability to perform basic automation and data visualization. Some applied knowledge in machine learning and AI techniques expected
• Product Knowledge - Demonstrate effective working knowledge and understanding of the payment products, with the ability to apply said knowledge for effective and efficient execution of the assignments
• Project Management - Demonstrate ability to effectively apply knowledge of Project Management for efficient execution and management of assigned tasks

3. Additional Requirements

• Adaptability and willingness to quickly pick up new programming languages and skills as needed
• Strong conceptual and analytical thinking skills
• Acts as an agent of change and stimulates others to change. Paves the way for needed changes; by taking calculated risks to derive maximum benefit
• Good written, presentation and communication skills; able to prepare statistical and narrative reports.
• Must be flexible and be able to participate in multiple projects simultaneously
• Able to work under broad direction while remaining resourceful and self-motivated to deliver work independently. Has technical responsibility and accountability for work performed and decisions taken
• Must possess excellent interpersonal skills and able to communicate and manage relationship at all levels with business users, financial institutions, vendors as well as team members