Staff Data Scientist, Revenue in London
Staff Data Scientist, Revenue

Staff Data Scientist, Revenue in London

London Full-Time 80000 - 100000 ÂŁ / year (est.) No home office possible
Airwallex

At a Glance

  • Tasks: Transform complex data into actionable insights and drive revenue growth with innovative AI solutions.
  • Company: Join a dynamic fintech company revolutionising global banking with cutting-edge technology.
  • Benefits: Competitive salary, diverse team culture, and opportunities for professional growth.
  • Other info: Work in Singapore and be part of a diverse, equal-opportunity employer.
  • Why this job: Make a real impact in a fast-paced environment while collaborating with exceptional teammates.
  • Qualifications: 7+ years in data science, strong analytical skills, and proficiency in SQL and Python.

The predicted salary is between 80000 - 100000 ÂŁ per year.

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

We’re looking for a talented Data Scientist who can push the boundaries of our existing models and help design state‑of‑the‑art solutions to GTM challenges that accelerate revenue growth and improve commercial efficiency. In this role, you’ll partner closely with Product, Growth, and Commercial teams to shape and build the next‑generation data science foundation at Airwallex. This role is based in Singapore.

Responsibilities

  • Translate complexity into action: Turn complex statistical and modeling results into clear, compelling, and actionable narratives for cross‑functional partners and executive audiences.
  • Uncover and scale revenue insights: Lead proactive, exploratory analyses to identify latent revenue levers, emerging trends, and root causes behind shifts in key GTM metrics—and operationalize these learnings into repeatable workflows, automated pipelines, and scalable data science operating models.
  • Build revenue forecasting and performance insights: Develop and own revenue forecasting and forward‑looking performance insights (e.g., pipeline health, conversion and retention drivers, scenario planning), providing a reliable “source of truth” that helps teams make faster, better commercial decisions.
  • Apply advanced causal inference: Use advanced observational causal inference methods (e.g., DiD, synthetic control, DoubleML) to estimate impact and inform decisions when randomized experiments are infeasible.
  • Embed AI into commercial workflows: Design and deploy AI‑enabled solutions across the sales and customer lifecycle—enhancing sales calls and coaching, improving sales effectiveness, and generating proactive, transaction‑based customer insights to drive retention and expansion.

Who You Are

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

Minimum Qualifications

  • 7+ years of industry experience and an advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics, or a related discipline).
  • Strong analytical intuition and structured problem‑solving—you ask the right questions, explore data thoughtfully, and synthesize clear, defensible conclusions.
  • Excellent communicator and storyteller—able to translate technical work into crisp, actionable recommendations for both technical and non‑technical stakeholders, including executives.
  • Deep curiosity about GTM performance and customer behavior—you go beyond “what happened” to understand “why it happened,” while staying pragmatic and focused on impact.
  • Strong foundations in causal inference and forecasting, with experience applying methods such as DiD, synthetic control, and modern ML‑based approaches to real business problems.
  • High fluency in analytics tooling—strong SQL skills and proficiency in Python and/or R for analysis, modeling, and automation.

Preferred Qualifications

  • Experience with Databricks or similar cloud data platforms / warehouses.
  • Familiarity with Hex or other notebook‑based analysis tools.
  • Experience in a high‑growth startup and/or B2B business models (e.g., pipeline, CRM, RevOps data).

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.

Staff Data Scientist, Revenue in London employer: Airwallex

At Airwallex, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership and drive impactful change. As a Staff Data Scientist in Singapore, you will collaborate with exceptional teams, leveraging cutting-edge AI technologies to solve complex challenges while enjoying ample opportunities for professional growth and development. Join us to be part of a forward-thinking company that values curiosity, innovation, and the pursuit of excellence in the global banking landscape.
Airwallex

Contact Detail:

Airwallex Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Data Scientist, Revenue in London

✨Tip Number 1

Network like a pro! Reach out to current employees on LinkedIn or through mutual connections. Ask them about their experiences and the company culture; it shows your genuine interest and can give you insider info that might help you stand out.

✨Tip Number 2

Prepare for the interview by diving deep into the company's mission and values. Think about how your skills align with their goals, especially in data science and revenue growth. Be ready to share specific examples of how you've tackled similar challenges in the past.

✨Tip Number 3

Practice your storytelling skills! You’ll need to translate complex data insights into clear narratives. Use the STAR method (Situation, Task, Action, Result) to structure your answers and make your experiences relatable and impactful.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team and helps us keep track of all applicants efficiently.

We think you need these skills to ace Staff Data Scientist, Revenue in London

Statistical Analysis
Causal Inference
Revenue Forecasting
Data Storytelling
SQL
Python
R
Analytical Intuition
Problem-Solving
AI Integration
Exploratory Data Analysis
Commercial Insight Development
Collaboration
Curiosity about GTM Performance
Experience with Cloud Data Platforms

Some tips for your application 🫡

Show Your Passion: When you're writing your application, let your enthusiasm for the role shine through! We want to see that you’re genuinely excited about the opportunity to make an impact and contribute to our mission.

Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure to highlight your relevant experience and skills without unnecessary fluff. Remember, less is often more!

Tailor Your Narrative: Make sure to connect your past experiences with the responsibilities outlined in the job description. We love seeing how your unique background can help us tackle complex challenges and drive revenue growth.

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!

How to prepare for a job interview at Airwallex

✨Know Your Numbers

As a Staff Data Scientist, you'll need to demonstrate your analytical prowess. Brush up on key metrics related to revenue growth and GTM performance. Be ready to discuss how you've used data to drive decisions in past roles, and think about specific examples where your insights led to tangible results.

✨Master the Art of Storytelling

You’ll be translating complex data into actionable narratives. Practice explaining your previous projects in a way that’s engaging and easy to understand for both technical and non-technical audiences. Use the STAR method (Situation, Task, Action, Result) to structure your responses and highlight your impact.

✨Showcase Your Curiosity

Demonstrate your deep curiosity about customer behaviour and GTM performance. Prepare questions that show you’ve done your homework on the company and its challenges. This not only shows your interest but also your proactive mindset in seeking solutions.

✨Familiarise with AI Applications

Since embedding AI into workflows is crucial for this role, be prepared to discuss how you've previously integrated AI solutions into your work. Think of specific tools or methods you've used, and be ready to share your thoughts on how AI can enhance sales effectiveness and customer insights.

Staff Data Scientist, Revenue in London
Airwallex
Location: London

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