Senior Data Analyst

Overview

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is

a place to do great work , offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also

a great place to work,

providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally. Responsibilities

Razer Gold aims to become the world’s leading payment service provider for games and digital content. As our business grows to meet the needs of gamers globally, we are seeking a highly skilled and detail-oriented Senior Data Analyst – Risk and Compliance to perform data-driven risk assessments and compliance monitoring initiatives. This role involves analyzing complex datasets to identify patterns, anomalies, and emerging risks that impact regulatory and internal compliance. The ideal candidate will have deep analytical expertise, experience in regulatory environments, and the ability to communicate insights clearly to stakeholders at all levels. Design, develop, and maintain reports and dashboards related to fraud risk, suspicious activity, transaction monitoring, and regulatory compliance. Build and enhance Power BI dashboards to visualize key AML and fraud KPIs (e.g., alert volumes, false positives, escalation rates). Analyze large datasets (transactions, customer behavior, device data) to detect anomalies, trends, and fraud patterns. Support the development of predictive risk models (e.g., fraud scoring, anomaly detection) using Python, pandas, scikit-learn, etc. Write and optimize complex SQL queries for extracting and transforming data from multiple fraud / AML-related systems. Collaborate with compliance officers, fraud investigators, data scientists, and product teams to gather requirements and build tailored data solutions. Conduct data validation, cleansing, and reconciliation to ensure accuracy of fraud / AML reporting and alert generation. Work closely with engineering teams to define and document data models Identify areas of improvement in alerting logic, rules tuning, or case management workflows through deep-dive analysis Partner with data engineering teams to improve data availability, reliability, and performance for analytics use cases Nice to Have

Experience in AML, fraud detection / prevention, financial crime investigations, or regulatory compliance within fintech, banking, or digital payments. Familiarity with AWS services commonly used in fraud and AML pipelines (e.g., S3, Lambda, Glue, Athena). Experience with cloud-based data platforms (AWS, GCP) for secure, scalable handling of sensitive transaction and customer data. Exposure to third-party fraud or AML platforms is a plus. Understanding of KYC, SARs, transaction monitoring, sanctions screening, or related AML regulations (e.g., BSA, FATF, OFAC). Requirements

Bachelor’s degree in Data Science, Computer Science, Information Systems, or related field. Minimum 3 years of experience in data analysis and business intelligence. Strong proficiency in Power BI (DAX, Power Query) and data modeling. Proficient in Python for data manipulation and report generation. Experience with SQL for working with relational databases. Experience with Agile Tools (JIRA, Confluence, BitBucket, Github) Excellent problem-solving skills. Strong communication skills and ability to work cross-functionally. Experience in handling financial datasets is a strong advantage. Team player with a proactive and accountable work attitude. Pre-Requisites

Are you game?

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