Senior Data Scientist, Anaytics (Risk & Compliance)

Airwallex2 weeks ago

Location

SG - Singapore

Type

Full Time

Level

Senior

Role

Data Engineer

Posted

Mar 2, 2026

Full TimeSenior

The role

Summary

Senior Data Scientist role at Airwallex Singapore focusing on regulatory compliance and financial crime analytics. The position involves building data foundations, validation frameworks, and self-service analytics for regulatory reporting across Airwallex's global fintech operations, requiring 5+ years of risk management experience and strong SQL/Python skills.

What you'll do

Regulatory Analytics Leadership: Lead analytics and data design for priority regulatory reports including regulatory compliance, financial crime, and financial regulatory returns from requirement translation through data logic, testing, and go-live

Cross-functional Data Standardization: Partner with Regulatory Compliance, FCC, Finance, DataOps and Data Engineering to standardize common dimensions (accounts, FX, products, entities) across reports using regulatory reporting data foundation

Quality Assurance Framework: Work with Data Engineering to define automated test suites and manual QA playbooks that must pass before reports are submitted to regulators

Historical Data Management: Leverage snapshotting and versioning approaches to ensure as-of historical reports can be regenerated and explained consistently during RFIs, audits, or supervisory exams

Root Cause Analysis: Conduct deep-dive analyses when anomalies, RFIs, or audit findings arise, quantifying impact, identifying root causes across products/entities, and proposing remediation options

Platform Requirements Definition: Shape requirements for a scalable regulatory reporting and risk analytics platform

Strategic Analytics Partnership: Lead cross-functional collaboration as primary analytics partner, turning open-ended regulatory and risk questions into structured analytical projects and roadmaps

Best Practices Champion: Champion best practices in analytical rigor, documentation, and validation for colleagues working on risk and compliance topics, providing informal mentorship to analysts and data scientists

What we look for

Technical

SQL Expertise5+ years of hands-on experience extracting and manipulating large data with SQL

Programming SkillsExperience with scripting in Python, Shell or R for data analysis and automation

Data VisualizationExperience building visualizations using large datasets and multiple data sources using Looker or Tableau

Risk Management SystemsProven experience with analytics, modeling implementation, and stakeholder management in risk contexts

Education

Quantitative DegreeBachelor's degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline

Experience

Risk Management Experience5+ years proven risk management experience or equivalent, including analytics, modeling implementation, and stakeholder management

Data Analysis Experience5+ years of hands-on experience with large-scale data extraction, manipulation, and analysis

Cross-functional CommunicationExcellent communication and stakeholder-management skills with ability to explain technical data topics to non-technical audiences and influence cross-functional partners

Skills

Required skills

SQLAdvanced proficiency in SQL for large-scale data extraction and manipulation

Python/R/ShellStrong scripting capabilities in at least one of Python, R, or Shell for data analysis

Data VisualizationProficiency with Looker or Tableau for creating complex visualizations from multiple data sources

Risk AnalyticsDeep understanding of risk management principles, analytics, and modeling implementation

Stakeholder ManagementExcellent communication skills to work with cross-functional teams and explain technical concepts to non-technical audiences

Nice to have

Regulatory ReportingDirect experience working on regulatory reporting for risk and compliance domains

Fintech Domain KnowledgeFamiliarity with fintech products including payments, FX, wallets, cards, and lending concepts

ML GovernanceExposure to model risk or AI/ML governance including model inventories, validation, and monitoring

Distributed Team ManagementExperience working with cross-functional, geographically distributed teams and managing by influence

Analytical Problem SolvingIntuitive, organized analytical thinking with ability to perform detailed analysis and use data to validate strategies

Compensation & benefits

Benefits

Global Impact

Work with a team of 2,000+ innovative professionals across 26 offices globally on high-impact fintech solutions

Career Growth

Accelerated learning opportunities and true ownership in a fast-growing $8 billion valued company

Innovation Focus

Access to cutting-edge AI tools and technologies to work smarter and solve problems faster

Collaborative Environment

Work with exceptional teammates in a collaborative, fast-paced environment with founder-like energy

Interview process

1
Application Review — Initial screening of resume and qualifications focusing on quantitative background and risk management experience
2
Technical Assessment — SQL and Python coding assessment with real-world data manipulation scenarios relevant to regulatory reporting
3
Case Study Presentation — Present analysis of a mock regulatory compliance scenario demonstrating analytical thinking and communication skills
4
Cross-functional Interview — Meet with stakeholders from Risk, Compliance, and Engineering teams to assess collaboration and influence capabilities
5
Leadership Interview — Final interview with senior leadership focusing on strategic thinking, mentorship potential, and cultural fit