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Senior Data Scientist, Analytics (Regulatory Reporting)

Airwallex

Singapore, Singapore, Singapore permanent

Posted: March 2, 2026

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Quick Summary

We are seeking a Senior Data Scientist, Analytics to join our team in Singapore. The ideal candidate will have a strong background in data analysis, programming languages, and data visualization. Key responsibilities will involve analyzing large datasets, identifying trends, and developing predictive models to drive business insights.

Job Description

About Airwallex

Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.

Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.

Attributes We Value

We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.

You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.

About the team

The Product team at Airwallex is a group of passionate builders and problem-solvers who are obsessed with crafting customer-centric solutions that empower businesses to operate anywhere, anytime. We combine technical expertise with a deep understanding of our customers' needs to design and build unified, intuitive, and scalable products. As a team, we thrive in a collaborative and fast-paced environment, constantly iterating and pushing boundaries to deliver exceptional product experiences.

We partner closely with legal, regulatory, financial crime compliance, product, engineering and commercial teams to help Airwallex grow safely and sustainably. Our work spans regulatory reporting, financial crime compliance, enterprise risk management, data & privacy and more – all under a fast-evolving global regulatory landscape. We’re a high-impact, high-trust team that thrives on solving complex problems to support Airwallex’s global ambitions.

What you'll do

As Senior Data Scientist, Analytics (Risk & Compliance), you will be the go-to analytics partner for our Regulatory Compliance and Financial Crime Compliance teams, impact across our global footprint. You’ll help transform how Airwallex manages regulatory reporting and risk oversight by building robust data foundations, validation frameworks, and self-service analytics that regulators, auditors, and senior leaders can rely on.

Responsibilities

• Lead analytics and data design for priority regulatory reports (e.g. regulatory compliance, financial crime, and financial regulatory returns), from requirement translation through to data logic, testing, and go‑live.

• Partner with Regulatory Compliance, FCC, Finance, DataOps and Data Engineering to standardise how we use common dimensions (accounts, FX, products, entities) across reports, leveraging the regulatory reporting data foundation.

• Work with Data Engineering to define automated test suites and manual QA playbooks that must pass before reports are submitted to regulators.

• Leverage snapshotting and versioning approaches so that “as‑of” historical reports can be regenerated and explained consistently during RFIs, audits, or supervisory exams.

• Conduct deep‑dive analyses when anomalies, RFIs, or audit findings arise – quantifying impact, identifying root causes across products/entities, and proposing remediation options.

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

• Lead cross‑functional collaboration, act as the primary analytics partner, turning open‑ended regulatory and risk questions into structured analytical projects and roadmaps.

• Champion best practices in analytical rigour, documentation, and validation for colleagues working on risk and compliance topics; provide informal mentorship to analysts and data scientists in adjacent teams.

Who you are

We're looking for people who meet the minimum requirements for this role. The preferred qualifications are great to have, but are not mandatory.

Minimum qualifications:

• Bachelor's degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline

• 5+ years proven risk management experience or equivalent, including analytics, modeling implementation, and stakeholder management

• 5+ years of hands-on experience extracting and manipulating large data with SQL, experience with scripting in Python, Shell or R

• Experience building visualizations using large datasets and multiple data sources using Looker or Tableau

• Excellent communication and stakeholder‑management skills: able to explain technical data topics to non‑technical audiences, document assumptions clearly, and influence cross‑functional partners across Legal, Risk, Compliance, Finance, and Engineering.

Preferred qualifications

• Direct experience working on regulatory reporting for risk and compliance domain

• Familiarity with data modelling for fintech products such as payments, FX, wallets, cards, and lending, including concepts like transaction lifecycles, balances, FX rates, stored value, and chargebacks.

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

• Intuitive, organized analytical thinker, with the ability to perform detailed analysis. Knowledge of analytical tools and use of data to validate strategies or hypotheses

• Experience working with cross-functional, geographically distributed teams, managing by influence is a plus

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.

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