Senior Data Scientist, Analytics (Regulatory Reporting)

The role

You will own the analytical layer of the regulatory data infrastructure. You will build systems to define and prove data correctness by working at the intersection of data engineering, compliance logic, and product intelligence.

What you will do

• Lead analytical and data design for priority regulatory reports
• Partner with compliance, finance, and engineering to standardise common dimensions
• Co-design data models and mart-layer logic with Data Engineering
• Define automated test suites and manual quality-assurance playbooks
• Investigate anomalies, requests for information, and audit findings
• Shape requirements for a scalable regulatory reporting and risk analytics platform
• Raise standards of analytical rigour, documentation, and validation
• Mentor analysts and data scientists in adjacent teams

Required qualifications

• 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 datasets with SQL
• Scripting experience in Python, Shell or R
• 5+ years of proven risk management experience or equivalent, including analytics, model implementation and stakeholder management
• Experience with analytics engineering practices, including writing modular, tested and documented SQL transformations using dbt or an equivalent tool
• Experience building exploratory and production-grade analytics with modern data tools, such as Hex, Evidence or notebook-style environments

Nice to have

• Direct experience working on regulatory reporting in risk and compliance domains
• Hands-on experience with dbt, including models, tests, documentation and macros, and a modern data warehouse such as BigQuery, Databricks or Snowflake
• Experience owning a data model end to end rather than only querying existing tables
• Understanding of data pipeline design and the ability to discuss trade-offs with Data Engineering peers
• Exposure to model risk or AI/ML governance, such as model inventories, validation and monitoring
• Experience working with cross-functional, geographically distributed teams and managing by influence

About the company

Airwallex is an AI-native financial operating system used by over 675,000 businesses. It provides financial infrastructure and regulated backbone for global payments across North America, Europe, the Middle East, and Asia-Pacific.