Senior Data Scientist, Analytics (Regulatory Reporting)

About the role

Airwallex, the AI-native financial operating system used by more than 675,000 businesses, is hiring a Senior Data Scientist, Analytics (Regulatory Reporting) for its Product team in Singapore. This is not a traditional reporting role: you will own the analytical layer of the regulatory data infrastructure, defining what "correct" means and building systems that prove it, at the intersection of data engineering, compliance logic and product intelligence. The role is based in Singapore, with the option to relocate.

Key responsibilities

• Lead analytics and data design for priority regulatory reports (regulatory compliance, financial crime, financial regulatory returns), from requirement translation through data logic, testing and go-live.
• Partner with Regulatory Compliance, FCC, Finance, DataOps and Data Engineering to standardise the use of common dimensions (accounts, FX, products, entities) across reports.
• Co-design data models and mart-layer logic with Data Engineering, taking part in how reporting dimensions are structured, tested and versioned upstream.
• Work with Data Engineering to define automated test suites and manual QA playbooks that must pass before regulator submissions.
• Run deep-dive analyses on anomalies, RFIs or audit findings, quantifying impact and proposing remediation.
• Shape requirements for a scalable regulatory reporting and risk analytics platform.
• Champion analytical rigour, documentation and validation, and mentor analysts and data scientists in adjacent teams.

Required profile

• Bachelor's degree in Mathematics, Statistics, Operations Research, Finance, Economics or a related quantitative discipline.
• 5+ years of hands-on experience extracting and manipulating large data with SQL, and scripting in Python, Shell or R.
• 5+ years of proven risk management experience or equivalent, including analytics, modelling implementation and stakeholder management.
• Ability to explain technical data topics to non-technical audiences and influence partners across Legal, Risk, Compliance, Finance and Engineering.

Required skills

• Familiarity with analytics engineering: modular, tested, documented SQL transformations (e.g. dbt or equivalent) and layered thinking (source, staging, marts).
• Exploratory and production analytics with modern data tools such as Hex, Evidence or notebook-style environments.
• Preferred: direct regulatory reporting experience, hands-on dbt and a modern data warehouse (BigQuery, Databricks or Snowflake), and exposure to model risk or AI/ML governance.