Risk Data Analytics Expert - Digital Bank

Monee; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

Monee is seeking a highly motivated Risk Data Analytics Expert in Singapore to enhance enterprise risk management across various risk types. The role involves designing risk data marts, optimizing data pipelines, and collaborating with stakeholders to ensure effective risk management solutions. Candidates should hold a Bachelor's degree in a relevant field and have at least 3 years of experience, alongside proficiency in SQL and Python. This position offers a dynamic work environment focused on continuous improvement.

Qualifications

• Minimum 3 years of experience in data engineering, data product management, or data analytics is preferred.
• Solid understanding of data warehousing architecture and data modeling concepts.
• Self-driven, adaptable, and able to thrive in a fast-paced environment.

Responsibilities

• Design, develop, and maintain robust risk data marts for risk reporting.
• Build and optimize data pipelines and automation solutions to enhance risk management.
• Partner with stakeholders to gather requirements and translate them into data solutions.

Skills

SQL

Python

Analytical thinking

Problem-solving

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Finance, Engineering or a related discipline

Job description

Job Description

We are seeking a highly motivated and analytical Risk Data Analytics Expert to strengthen and scale our enterprise risk management capabilities across Fraud Risk, Credit Risk, Market & Liquidity Risk, and Operational Risk in our digital banks.

In This Role, You Will

• Design, develop, and maintain robust risk data marts to serve as the single source of truth for risk reporting, analytics, and modelling.
• Build and optimize data pipelines, tools, and automation solutions to enhance the accuracy, efficiency, and scalability of risk management processes.
• Provide reliable business-as-usual (BAU) support to ensure the stability and integrity of risk data and reporting workflows.
• Partner closely with risk, technology, and business stakeholders to gather requirements and translate them into scalable data solutions.
• Drive end-to-end solution delivery, effectively bridging risk and technology teams.
• Perform data and system analysis to identify enhancement opportunities, improve data quality, and streamline operational processes.
• Contribute to continuous improvement initiatives that elevate risk data governance and control standards.

Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, Finance, Engineering or a related discipline.
• Minimum 3 years of experience in data engineering, data product management, or data analytics is preferred.
• Proficiency in SQL and Python for data transformation, automation, and analytics.
• Solid understanding of data warehousing architecture and data modeling concepts.
• Strong analytical thinking and problem-solving skills with attention to detail.
• Effective communication skills with the ability to engage and manage cross-functional stakeholders.
• Self-driven, adaptable, and able to thrive in a fast-paced environment.
• Experience in Agent engineering or AI-driven process automation is a plus.