At a Glance
- Tasks: Transform complex data into actionable insights and drive revenue growth with innovative AI solutions.
- Company: Join a forward-thinking fintech company revolutionising global banking.
- Benefits: Competitive salary, flexible work options, and opportunities for rapid career advancement.
- Other info: Diverse and inclusive workplace committed to equal opportunity.
- Why this job: Make a real impact in a dynamic environment while collaborating with exceptional teammates.
- Qualifications: 7+ years in data science with strong analytical and communication skills.
The predicted salary is between 70000 - 90000 € 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, Sales Analytics in London employer: Airwallex
At Airwallex, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership of their projects and drive real impact. Located in the vibrant city of Singapore, our team thrives on collaboration and innovation, offering exceptional growth opportunities through hands-on experience with cutting-edge AI technologies. Join us to tackle complex challenges alongside talented colleagues while enjoying a supportive environment that values diversity and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Scientist, Sales Analytics 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 insights into the company culture. This not only shows your interest but can also 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 in data science can directly contribute to their goals. Be ready to share specific examples of how you've tackled complex problems in the past—this will show you're the right fit for their team.
✨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 responses during interviews, making it easier for interviewers to see your impact.
✨Tip Number 4
Don’t forget to follow up after your interview! A quick thank-you email reiterating your enthusiasm for the role can leave a lasting impression. Plus, it’s a great opportunity to mention anything you forgot to say during the interview.
We think you need these skills to ace Staff Data Scientist, Sales Analytics in London
Some tips for your application 🫡
Show Your Passion:When 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 in sales analytics and how you can contribute to our mission.
Be Clear and Concise:We appreciate a straightforward approach. Make sure to communicate your experiences and skills clearly, focusing on how they relate to the responsibilities outlined in the job description. Avoid jargon and keep it simple!
Highlight Relevant Experience:Tailor your application by emphasising your experience with data science, causal inference, and revenue forecasting. We’re looking for specific examples that demonstrate your analytical intuition and problem-solving skills—make them stand out!
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 sales analytics and be ready to discuss how you've used data to drive decisions in the past. Prepare specific examples that showcase your ability to translate complex data into actionable insights.
✨Master the Art of Storytelling
You’ll be expected to communicate technical findings to non-technical stakeholders. Practice explaining your previous projects in a way that highlights the impact of your work. Use clear narratives that connect your data insights to business outcomes, making it relatable for everyone in the room.
✨Show Your Curiosity
Demonstrate your deep curiosity about GTM performance and customer behaviour. Prepare questions that show you’re not just interested in what happened, but why it happened. This will reflect your analytical intuition and structured problem-solving skills, which are crucial for this role.
✨Familiarise with AI Applications
Since embedding AI into commercial workflows is part of the job, be ready to discuss how you've previously applied AI or machine learning in your projects. Highlight any experience with causal inference methods and how they can be used to solve real business problems, showcasing your technical expertise.
