Europe Arbeitnow ·
full-timeStaff Data Scientist
Airwallex · UK - London
Airwallex is an AI-native financial operating system providing infrastructure for global commerce, payments, and financial operations. As a Staff Data Scientist based in London, you will play a senior role in shaping the company's analytical strategy and technical direction. Your daily responsibilities will involve leading complex analytical projects, mentoring team members, and evolving data science from standalone analyses into scalable decision-support systems. You will act as a strategic partner to cross-functional teams, using quantitative analysis, forecasting, and data storytelling to influence business investment and operational decisions. This role requires an expert-level proficiency in SQL, Python, or R, and the ability to navigate ambiguity while owning project roadmaps. The position is well-suited for a seasoned professional with over eight years of industry experience and an advanced degree in a quantitative field who excels at simplifying complex data into actionable insights. You will be expected to work from the London office three days a week, contributing to both the analytical and algorithmic capabilities that optimize the company's financial platforms.
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 2,300 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. How you'll make impact As a Staff Data Scientist, you'll help Airwallex make better strategic and operational decisions through rigorous analysis, forecasting, and clear data storytelling. You'll combine hands-on analytical leadership with strategic influence, helping evolve data science into a more scalable, general capability across the business. Uplevel the data science team through technical mentorship, hands-on leadership on complex analytical problems, and a clear vision for the team’s longer-term direction. Act as a strategic thought partner to cross-functional teams, using data and technical expertise to inform, influence, and execute strategy and investment decisions. Apply quantitative analysis, data mining, forecasting, and clear data storytelling to answer important business questions and guide strategic decisions. Define goals, build forecasts, and monitor key business metrics to identify trends and assess performance across the organisation. Help evolve data science from individual analyses into scalable systems of decision support, establishing robust analytical approaches that produce reliable insights repeatedly. You'll work from our London office three days a week. What we're looking for Essentials 8+ years of industry experience. An advanced degree, such as a PhD or MS, in a quantitative field such as Statistics, Engineering, Sciences, Computer Science, or Economics. Experience communicating analytical results to leadership and cross-functional teams to influence strategy. Experience providing technical mentorship in data science or quantitative analysis in an industry setting. Expert-level ability in data-querying languages such as SQL, scripting languages such as Python, and/or statistical or mathematical software such as R. 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 with ambiguity. Give you a problem, not a prescription, and you'll run with it. You connect dots across functions and hold the big picture without losing grip on the details. You simplify complexity rather than hiding behind it. Learn more about your team Data Science at Airwallex is evolving from individual analyses and standalone models into scalable systems of decision and action. We bring together two complementary capabilities: DS Analytics, which improves decision quality and reduces decision latency, and DS Algorithm, which directly optimizes product and business outcomes in real time. You’ll build systems of decision that help teams understand what changed, determine what to do next, and learn whether the action worked. This means owning the AI analytics harness around the analysis—including semantic layers, context retrieval, evaluation infrastructure, validation gates, and governance—so decisions remain reliable, contextualized, and trustworthy at scale. You’ll also build systems of action that use machine learning and AI to shape product behavior, ranking, pricing, risk, allocation, and customer experiences. The work extends beyond training models to designing how intelligent systems reason, use tools, operate within guardrails, execute workflows, and measure their incremental impact. As AI makes ad hoc analysis increasingly accessible, the remaining advantage is scale, scientific method, and rigor. You’ll structure ambiguous problems, design experiments, identify confounding factors, challenge misleading conclusions, and build production systems that produce reliable outcomes repeatedly—not just one-off answers. The work is moving up the stack: from analysis to system, from model to harness, and from answering a question once to building something that answers it correctly over time. If you want to create data science systems that compound decision quality and turn intelligence into measurable action, this is where that work happens. Applicant Safety Policy: Fraud and Third-Party Recruiters To protect you from recruitment scams, please be
| Role | Staff Data Scientist |
|---|---|
| Company | Airwallex |
| Location | UK - London |
| Type | full-time |
| Compensation | Not disclosed |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4More at Airwallex
Other jobs at Airwallex
- Director, Sanctions · UK - London
- Sales Manager, SME & Growth · UK - Manchester
- Senior Software Engineer, Payments Platform · NL - Amsterdam
- Associate Director, Transaction Monitoring · UK - London
- Associate Director, KYC · UK - Birmingham
Explore Related Placements
// similar opportunities
You might also like
Staff Data Scientist
Monzo
🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a pr...
Staff Data Scientist
Servicenow
No description available.
Data Scientist
Insurity Solutions India Private Limited
Data Scientist at Insurity Solutions India Private Limited 2 candid answers 1 video Posted by Sagar Das Apply now Remote, Noida · 2 - 5 years · ₹22L - ₹30L / yr...
Data Scientist
Kayak
KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world's leading travel search engine. With billions of queries across our platforms, we help people find ...
Data Scientist
Physicsx
About us Re-architecting Engineering for the Age of Intelligence PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hard...
Data Scientist
Wave
Our mission We're making Africa the first cashless continent. In 2017, over half the population in Sub-Saharan Africa had no bank account. That's for good reaso...