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Airwallex

Senior Data Scientist, Anaytics (Risk & Compliance)

Posted One Month Ago
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In-Office
Singapore, SGP
Senior level
In-Office
Singapore, SGP
Senior level
Lead analytics and data design for regulatory reporting and financial crime compliance. Build data models, validation frameworks, automated testing, QA playbooks, and self-service analytics in partnership with Compliance, Finance, DataOps, and Engineering. Investigate anomalies and audit findings, identify root causes, shape risk analytics platforms, and promote analytical rigor and documentation across global teams.
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About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

 
How you'll make impact

This isn’t a traditional reporting role. You’ll own the analytical layer of Airwallex’s regulatory data infrastructure, defining what “correct” means and building systems that prove it. You’ll work at the intersection of data engineering, compliance logic and product intelligence to help transform how Airwallex manages regulatory reporting and risk oversight.

  • Lead the analytical and data design for priority regulatory reports, translating requirements into data logic, testing and go-live processes.

  • Partner with Regulatory Compliance, Financial Crime Compliance, Finance, Data Operations and Data Engineering to standardise common dimensions such as accounts, FX, products and entities across reports.

  • Co-design data models and mart-layer logic with Data Engineering, shaping how reporting dimensions are structured, tested and versioned upstream.

  • Define automated test suites and manual quality-assurance playbooks that reports must pass before submission to regulators.

  • Investigate anomalies, requests for information and audit findings by quantifying impact, identifying root causes across products and entities, and proposing remediation options.

  • Shape requirements for a scalable regulatory reporting and risk analytics platform.

  • Raise the standard of analytical rigour, documentation and validation across risk and compliance topics, while mentoring analysts and data scientists in adjacent teams.

This is an in-office role — you’ll be in our Singapore office five days a week.

What we’re looking for

Essentials

  • A 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, plus 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, and thinking in layers across sources, staging and marts.

  • Experience building exploratory and production-grade analytics with modern data tools, such as Hex, Evidence or notebook-style environments where SQL, Python and visualisation work together.

  • Excellent communication and stakeholder-management skills, with the ability to explain technical data topics to non-technical audiences, document assumptions clearly and influence partners across Legal, Risk, Compliance, Finance and Engineering.

Preferred

  • 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, including when a problem belongs in the transformation, application or reporting layer, and the ability to discuss these trade-offs with Data Engineering peers.

  • Exposure to model risk or AI/ML governance, such as model inventories, validation and monitoring, and an interest in how these frameworks intersect with regulatory reporting and compliance analytics.

  • Experience working with cross-functional, geographically distributed teams and managing by influence.

You’ll thrive here if
  • You're comfortable owning the roadmap yourself.

  • You own the outcome and you don't wait for permission to fix what's broken.

  • You're comfortable making decisions with incomplete information and moving quickly anyway.

  • You simplify complexity rather than hiding behind it.

  • You communicate clearly and directly across cultures, and you're thoughtful about how context shifts meaning across borders.

Learn more about your team

The Regulatory Reporting team at Airwallex owns one of the most consequential data functions in the company: ensuring our financial activities are reported accurately, completely, and on time to regulators and central banks in every jurisdiction where we hold a license. We're platform engineers and data professionals who own the full regulatory reporting lifecycle, from interpreting requirements and building the pipelines that produce filings, to submission, tracking, and maintaining an audit trail that holds up to scrutiny. We partner closely with Regulatory Compliance, Legal, Finance Operations, and Product, using modern data tooling, cloud infrastructure, and increasingly AI-driven automation to make that lifecycle reliable and efficient at scale. If you're motivated by problems that are technically demanding, operationally high-stakes, and genuinely global, we'd like to meet you.

Applicant Safety Policy: Fraud and Third-Party Recruiters

To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.

HQ

Airwallex Singapore, Singapore, SGP Office

Airwallex Singapore Office

Airwallex’s global HQ is nestled in the tallest building in Singapore, at the centre of the city state’s vibrant Tanjong Pagar district. Opened in February 2023, the Airwallex Singapore office is a bustling hub of culture, innovation and collaboration, and home to dynamic, diverse teams.

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