Senior Risk Analytics Engineer: Fraud Detection & Monitoring

SNSOFT SDN. BHD.; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Benefits offered by this job

13th Month Salary

Project Incentive

Sports Activities (Badminton &Basket)

Training sponsorship

Medical Insurance

Optical, Dental, Body Check Up

Job summary

SNSoft SDN BHD is seeking a Senior Data Analytics Engineer (Risk Analytics) to join our Data & Analytics team. You will detect abnormal behaviour, design risk detection strategies, and deliver data solutions for risk management and business decisions.

The role involves analyzing large-scale transaction data and identifying suspicious activities, fraud, and abuse patterns. You will build ETL/ELT pipelines and automate risk monitoring, dashboards, and alerts.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, or related field.
• 5+ years of relevant experience in Data Analytics, Data Engineering, Risk Analytics, or related roles.
• At least 2 years of hands-on experience in Risk Analytics, Fraud Detection, Transaction Monitoring, or Risk Strategy Development.
• Strong proficiency in SQL and Python (mandatory), including complex data analysis, automation, and query/performance optimization.
• Proven experience identifying suspicious behavioral patterns and developing or optimizing risk detection rules or strategies.
• Strong understanding of statistical analysis, anomaly detection, and data-driven decision-making.
• Practical experience with ETL/ELT, data warehousing, and large-scale datasets.
• Experience with relational or analytical databases such as PostgreSQL, MySQL, ClickHouse, or equivalent technologies.
• Ability to independently investigate complex problems, identify root causes, and propose practical solutions.
• Strong analytical thinking, problem-solving, communication, and stakeholder management skills.

Responsibilities

• Join our Data & Analytics team to detect abnormal behaviour, build risk detection strategies, and deliver reliable data solutions for risk management and business decisions.
• Analyze large-scale transaction and user behavioral data to identify suspicious activities, abnormal patterns, and potential business risks.
• Design, develop, and continuously optimize risk detection rules, monitoring strategies, and analytical frameworks.
• Identify fraud, abnormal transactions, promotional abuse, arbitrage or exploitation patterns, and other suspicious user behaviors.
• Apply statistical analysis, anomaly detection, and behavioral analysis to improve risk detection capabilities.
• Evaluate and optimize risk strategies based on detection accuracy, false-positive rates, precision/recall, and business impact
• Investigate risk incidents, perform root-cause analysis, and recommend preventive or corrective actions.
• Data Engineering & Advanced Analytics: Design and maintain scalable ETL/ELT pipelines, datasets, and data models supporting risk analytics and monitoring.
• Write and optimize complex SQL queries and Python scripts for large-scale data processing, investigation, and automation.
• Integrate and analyze data from multiple sources, including transactional databases, event logs, APIs, and third-party systems.
• Perform exploratory data analysis, statistical analysis, and behavioral pattern analysis.
• Ensure data quality, consistency, reliability, and processing efficiency.
• Partner with Risk, Operations, Product, and Engineering teams to translate business risk scenarios into technical and analytical solutions.
• Provide actionable recommendations based on analytical findings.
• Communicate complex analytical and risk-related insights clearly to both technical and non-technical stakeholders.
• Contribute to team best practices and mentor junior team members when required.
• Develop automated risk monitoring solutions, dashboards, alerts, and recurring analytical workflows.
• Define and optimize statistical thresholds and anomaly detection methodologies.
• Monitor key risk indicators and proactively identify emerging risk patterns.
• Automate recurring risk analysis, validation, and reporting processes.
• Continuously improve monitoring coverage, alert accuracy, and operational efficiency.

Skills

SQL

Python

Analytical thinking

Stakeholder management

Data analysis

Education

Bachelor’s degree in Computer Science or related field

Tools

PostgreSQL

MySQL

ClickHouse

Kafka

Flink

Tableau

Power BI

Alibaba Cloud

AWS

GCP

Azure

Job description

SNSoft SDN BHD is seeking a Senior Data Analytics Engineer (Risk Analytics) to join our Data & Analytics team. You will detect abnormal behaviour, design risk detection strategies, and deliver data solutions for risk management and business decisions.

The role involves analyzing large-scale transaction data and identifying suspicious activities, fraud, and abuse patterns. You will build ETL/ELT pipelines and automate risk monitoring, dashboards, and alerts.