← All jobs
Airwallex

Staff Data Scientist, Algorithm (Payments Fraud & Optimization)

SG - Singapore
Level
Staff
Work type
On-site · SG

Not stated in the posting: salary, visa.

Open. First seen 2 October 2026.

About the role

About Airwallex

Airwallex's standard text

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 2,300 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.

About the Role:
We are seeking a highly skilled and experienced Staff Data Scientist to drive the technical direction of our Payments Optimization team. This is a critical Individual Contributor (IC) role that will focus on designing and implementing advanced algorithms to optimize payments. You will act as a key strategic partner to Product, Engineering, and Commercial leaders, identifying complex, unique opportunities to improve payments performance and drive product adoption at scale.

Responsibilities:

  • Define and drive the technical strategy for multi-objective payments optimization, ensuring that AWX optimizes payment conversion rates, fraud risk, and transaction costs.
  • Act as the strong technical owner on cross-functional initiatives, solving unique, critical, and complex problems that have a broad impact on the business.
  • Provide technical thought leadership on various optimization algorithms (e.g. contextual bandits) and experimentation techniques (e.g. A/B testing, causal inference).
  • Collaborate with engineering teams to design and build tools and infrastructure to enable optimization at scale and deploy ML systems to production.
  • Partner with Product, Engineering, Risk, and other cross-functional teams to inform and influence product strategy and investment decisions.
  • Clearly and persuasively communicate complex data insights and technical recommendations to both technical and non-technical audiences, ensuring your findings influence stakeholders at all levels.
  • Mentor and coach junior data scientists and engineers.

Qualifications:

  • Advanced degree (PhD or MS) in a quantitative field such as Statistics, Engineering, Computer Science, Economics, or related disciplines.
  • 5+ years of industry experience in data science or applied ML.
  • Proven experience in experimentation and causal inference to drive data-informed product decisions with concrete impact.
  • Strong experience in deploying ML systems to production is a big plus.
  • Demonstrated ability to operate as a technical leader, defining and developing critical systems and influencing product strategy in high-growth environments.
  • Proficient in SQL and Python/R.
  • Experience using LLM, AI and Agent to improve processes and ML models

Why Join Us:

  • Opportunity to work on impactful problems that directly influence payments success and business outcomes.
  • Collaborate with a talented, cross-functional team in a fast-paced, high-growth environment.
  • Drive the adoption of advanced data science techniques and experimentation to improve customer and business outcomes.

Applicant Safety Policy: Fraud and Third-Party Recruiters

Airwallex's standard text

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.

What this role asks for

Standard for data science / ML roles

LLM · Machine Learning · Python · SQL

Common in data science / ML postings at any company.

71% of this description is written for the role. The rest is Airwallex's standard text, folded away below.

Read against Airwallex's other open postings on this site.

The team: Risk Platform HIRES STEADILY

This role is one of 17 open in Risk Platform. 3 were posted in the last 30 days and the oldest in September: a team that hires all year rather than one being built.

WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS

Machine Learning (11 of 17), LLM (10 of 17), Python (9 of 17), Java (7 of 17), Kotlin (6 of 17), SQL (6 of 17), AWS (5 of 17)

OTHER ROLES ON THIS TEAM

From the team and dates on Airwallex's own job board.

Similar jobs

Is this your posting and you want it taken down? Email info@careerholo.com.