Airwallex

About Airwallex

Empowering businesses with seamless cross-border payments

🏢 Tech, Finance👥 1001+ employees📅 Founded 2015📍 Fitzrovia, London, UK💰 $1.2b3.8
FintechB2BBankingForeign exchangeFinancial Services

Key Highlights

  • Valuation exceeds $5 billion with $1.2 billion raised
  • Over 20,000 corporate customers using its services
  • Headquartered in Fitzrovia, London, UK
  • Offers corporate cards and expense management solutions

Airwallex, founded in 2015 and headquartered in Fitzrovia, London, is a leading fintech company specializing in cross-border payments and foreign exchange solutions. With a valuation exceeding $5 billion, Airwallex has raised $1.2 billion in funding and serves over 20,000 corporate customers, provid...

🎁 Benefits

Employees enjoy a flexible work environment with 3 months of 'work from anywhere' policy each year, along with on-site meals and snacks to enhance wor...

🌟 Culture

Airwallex fosters a culture focused on simplifying global financial transactions for businesses, aiming to disrupt traditional banking with competitiv...

Overview

Airwallex is hiring a Data Scientist, Algorithm (Growth) to tackle complex problems and drive growth through data-driven insights. You'll work with Python, SQL, and machine learning techniques in San Francisco.

Job Description

Who you are

You have a strong background in data science with expertise in algorithms and machine learning — you've successfully applied these skills to drive growth and improve business outcomes. Your proficiency in Python and SQL allows you to manipulate and analyze large datasets effectively, and you have a keen eye for data visualization that helps communicate insights clearly to stakeholders.

You thrive in collaborative environments and enjoy working with cross-functional teams — your ability to communicate complex technical concepts to non-technical audiences sets you apart. You are driven by curiosity and a desire to solve challenging problems, always looking for innovative ways to leverage data for strategic decision-making.

Your experience includes developing and implementing machine learning models that enhance product features and user experiences — you understand the importance of data quality and are skilled in data cleaning and preprocessing techniques. You are comfortable working with various data tools and platforms, and you stay updated on the latest trends in data science and analytics.

Desirable

Experience with cloud platforms like AWS or GCP is a plus, as is familiarity with big data technologies such as Apache Spark. You may also have a background in financial services or payments, which would be beneficial in understanding the domain-specific challenges faced by Airwallex.

What you'll do

As a Data Scientist at Airwallex, you will be responsible for analyzing complex datasets to derive actionable insights that drive growth. You will collaborate closely with product managers and engineers to identify key metrics and develop algorithms that enhance user acquisition and retention strategies. Your role will involve building predictive models and conducting A/B testing to evaluate the effectiveness of new features.

You will also be tasked with creating data visualizations and dashboards that communicate findings to stakeholders across the organization — your insights will help shape product development and marketing strategies. Additionally, you will mentor junior data analysts and contribute to the overall data strategy of the company, ensuring that data-driven decision-making is at the forefront of Airwallex's operations.

What we offer

Airwallex provides a dynamic work environment where you can make a significant impact on the company's growth trajectory. You will have access to cutting-edge tools and technologies, and the opportunity to work alongside some of the brightest minds in the industry. We offer competitive compensation and benefits, including flexible working arrangements to support your work-life balance. Join us in building the future of global payments and financial solutions.

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