Senior Data Scientist, Analytics (Lending)
Data Scientist · Senior · Full Time
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Role
What you'll do.
As a Senior Data Scientist specializing in Analytics for Airwallex's Lending division, you will drive data-driven decision-making across credit risk management and portfolio optimization. Working within the Risk Platform team at this $11 billion fintech leader, you will design and implement advanced analytical frameworks, credit risk models, and performance monitoring systems that directly influence lending outcomes for over 250,000 global businesses. This role requires deep expertise in credit risk analytics, statistical modeling, and cross-functional collaboration to translate complex portfolio challenges into actionable insights that improve credit quality and support sustainable growth in the lending business.
Responsibilities
- Portfolio Performance Monitoring and Analysis: Monitor and analyze the performance of existing business lending portfolios through advanced data analytics, tracking delinquency trends, early warning indicators, and credit quality metrics. Identify emerging risks within the portfolio and provide actionable insights to mitigate potential losses and optimize portfolio composition.
- Credit Risk Strategy and Optimization: Support the assessment and optimization of portfolio-level credit strategies, ensuring alignment with regional credit risk policies and regulatory requirements. Design and refine credit decision frameworks that balance growth objectives with risk management.
- Advanced Analytics and Modeling: Develop and maintain predictive models, including Expected Credit Loss (ECL) models, credit risk assessment frameworks, and stress testing methodologies. Translate complex statistical concepts into practical tools that support credit quality decisions and policy optimization.
- Risk Dashboard and Reporting Development: Design and prepare comprehensive portfolio reports, interactive risk dashboards, and management summaries to support senior leadership decision-making. Ensure data visualization and reporting infrastructure enable real-time monitoring of credit performance metrics.
- Cross-Functional Collaboration and Implementation: Collaborate with Operations, Product, and Policy teams to ensure consistent application of credit policies, effective risk controls, and data-driven governance. Translate business requirements into analytical solutions and provide technical support for policy implementation across lending channels.
- Regulatory Compliance and Governance: Participate in periodic portfolio reviews, stress testing exercises, and comprehensive credit risk assessment activities. Provide analytical support for regulatory reporting, audits, and internal governance requirements to maintain compliance with financial services regulations.
- Data Quality and Research: Conduct deep-dive analysis of large datasets using advanced SQL and Python capabilities. Identify data discrepancies, validate model assumptions, and perform exploratory data analysis to uncover insights that drive portfolio optimization strategies.
Qualifications
What we look for.
Technical
SQL Proficiency
Advanced SQL skills for querying, aggregating, and transforming large financial datasets. Ability to write complex queries involving multiple joins, window functions, and performance optimization for analytical workloads.
Python Programming
Proficient Python development for data analysis, statistical modeling, and machine learning. Experience with libraries such as pandas, scikit-learn, statsmodels, and NumPy for implementing credit risk models and analytical frameworks.
Statistical Modeling and Analysis
Strong foundation in statistical methodologies including regression analysis, classification models, time series analysis, and hypothesis testing. Experience building and validating predictive models for credit risk assessment.
Credit Risk Modeling
Experience developing Expected Credit Loss (ECL) models, probability of default (PD) models, loss given default (LGD) frameworks, or equivalent credit risk quantification methodologies.
Data Visualization and BI Tools
Ability to communicate data insights through effective visualizations. Familiarity with business intelligence tools such as Tableau, Looker, Power BI, or similar platforms for creating executive dashboards.
Education
Bachelor's Degree in Quantitative Discipline
Bachelor's degree or above in Quantitative Finance, Statistics, Computer Science, Business Analytics, Data Science, Applied Mathematics, or related quantitative field with strong mathematical foundations.
Experience
Credit Risk Analytics Experience
3+ years of professional experience in credit risk analytics, portfolio risk analysis, credit strategy development, or related quantitative roles within financial services or fintech organizations.
Large-Scale Data Analysis
Proven track record working with large, complex financial datasets using SQL and Python. Demonstrated ability to translate raw data into meaningful insights and actionable recommendations for business stakeholders.
Problem-Solving with Financial Data
Experience identifying and solving complex business problems using analytical approaches. Strong attention to detail in data quality validation and discrepancy identification critical for regulatory compliance and risk management.
Cross-Functional Collaboration
Experience partnering effectively with non-technical stakeholders including risk management, operations, product, and compliance teams. Ability to communicate technical concepts clearly to diverse audiences.
Skills
Required
SQL
Expert-level SQL for complex analytical queries, data extraction, and transformation from relational databases used in lending and risk analytics systems.
Python
Production-grade Python coding for data analysis, statistical modeling, and developing credit risk analytics frameworks and tools.
Statistical Analysis
Advanced statistical methods including regression, classification, and hypothesis testing applied to credit risk and portfolio analysis problems.
Data Analysis and Interpretation
Ability to extract actionable insights from complex datasets, identify patterns, and communicate findings to support data-driven decision-making.
Business Problem Solving
Analytical mindset to break down complex credit risk and portfolio optimization challenges into structured, data-driven solutions.
Preferred
ECL Modeling
Nice to haveHands-on experience building and implementing Expected Credit Loss models under accounting standards such as IFRS 9 or ASC 326 for financial institutions.
SME Lending Experience
Nice to haveSpecialized knowledge of small and medium enterprise lending, including underwriting criteria, default patterns, and portfolio dynamics in the SME lending market.
Credit Risk Assessment and Modeling
Nice to haveAdvanced expertise in probability of default (PD), loss given default (LGD), exposure at default (EAD) modeling and credit risk quantification methodologies.
Credit Policy and Decision Strategy Design
Nice to haveExperience designing credit policies, decision trees, approval strategies, or performance monitoring frameworks that balance risk and growth objectives.
Stress Testing and Regulatory Reporting
Nice to haveFamiliarity with stress testing frameworks, regulatory reporting requirements, governance processes, and audit methodologies for financial services organizations.
Risk Analytics and Modeling Hybrid Role
Nice to haveCombined experience in both risk analytics and quantitative modeling, with ability to bridge business insights and mathematical sophistication.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 120,000 – 180,000
Equity·Stock options
Benefits
Impact-Driven Work
Opportunity to work on high-impact credit risk problems that directly influence lending portfolio performance and business outcomes for over 250,000 global businesses.
Talented Cross-Functional Team
Collaborate with a highly skilled, diverse team of engineers, product managers, and risk professionals in a fast-paced, high-growth environment within a $11 billion fintech leader.
Career Growth and Learning
Accelerated learning opportunities through work on complex, high-visibility problems in global payments and financial infrastructure, with mentorship from industry experts.
Founder-Like Ownership
True end-to-end ownership of analytical projects, from problem definition through implementation and impact measurement, with autonomy to drive decisions.
Global Scale and Exposure
Work across Airwallex's global lending operations spanning 27 offices worldwide, gaining exposure to diverse lending markets, regulatory environments, and customer segments.
AI-Driven Problem Solving
Access to cutting-edge AI and machine learning tools to enhance analytical capabilities, automate routine tasks, and focus on higher-value strategic analysis.
Process
Interview steps.
- 01
Initial Screening Call
Conversation with the recruiting team to discuss your background in credit risk analytics, data science experience, and alignment with Airwallex's mission and operating principles. Expected duration: 30 minutes.
- 02
Technical Assessment
Hands-on technical evaluation of SQL and Python proficiency through practical exercises. You'll work through real analytical problems similar to those encountered in the role, demonstrating your ability to query data, analyze patterns, and solve credit risk-related challenges. Expected duration: 60-90 minutes.
- 03
Case Study and Problem-Solving
In-depth case study on a credit risk or portfolio analytics scenario. You'll receive a dataset or business problem and develop an analytical approach, presenting your methodology, findings, and recommendations to the hiring team.
- 04
Team and Manager Interview
Interviews with your potential manager and key team members from the Risk Platform team. Discussions will focus on your experience with cross-functional collaboration, credit risk strategy, and your approach to translating business problems into analytical solutions.
- 05
Behavioral and Culture Fit Discussion
Conversation exploring your alignment with Airwallex's values of builder mentality, first-principles thinking, end-to-end ownership, and collaborative problem-solving in fast-paced environments.
Full posting
Original listing.
About Airwallex
Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 250,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.
Proudly founded in Melbourne, we have a team of over 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.
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
The risk platform team at Airwallex is responsible for managing risk across all Airwallex products, including topics like lending, Payments, Issuing and Onboarding. The risk landscape is constantly changing, and threats are becoming increasingly sophisticated. We are at the forefront of innovation in risk management.
What you’ll do
As a Credit Risk Analyst - Lending, you will help monitor and optimize the performance of Airwallex’s business lending portfolio through data-driven analysis, portfolio insights, and credit risk strategy support. You will be responsible for translating portfolio and policy questions into analytical frameworks, monitoring approaches, and actionable recommendations that improve credit quality and support sustainable business growth.
Responsibilities:
Monitor and analyze the performance of existing business lending portfolios, including delinquency trends, early warning indicators, and credit quality metrics
Identify emerging risks within the portfolio and provide actionable insights to mitigate potential losses
Support the assessment and optimization of portfolio-level credit strategies, ensuring alignment with regional credit risk policies
Prepare portfolio reports, risk dashboards, and management summaries to support senior leadership decision-making
Collaborate with Operations and Product teams to ensure consistent application of credit policies and effective risk controls
Participate in periodic portfolio reviews, stress testing, and credit risk assessment exercises
Provide analytical support for regulatory reporting, audits, and internal governance requirements
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:
3+ years of experience in credit risk analytics, risk strategy, portfolio analytics, or a related quantitative role
Bachelor’s degree or above in Quantitative Finance, Statistics, Computer Science, Business Analytics, Data Science, or a related quantitative discipline
Proficient in SQL and Python, with the ability to translate data into actionable insights
Strong problem-solving skills and experience working with large datasets
Strong attention to detail and the ability to identify discrepancies in data
Experience partnering with cross-functional stakeholders to solve business problems
Preferred qualifications:
Hybrid experience of both risk analytics and modelling
Experience in SME lending experience preferred
Hands-on experience in ECL modelling, credit strategy analysis, or credit risk assessment
Experience designing credit policies, decision strategies, or performance monitoring frameworks
Familiarity with stress testing, governance, audit, or regulatory reporting processes
Why Join Us:
Opportunity to work on impactful credit risk problems that directly influence lending performance and business outcomes.
Collaborate with a talented, cross-functional team in a fast-paced, high-growth environment.
Drive better portfolio decisions through analytics, monitoring, and risk insights that improve customer and business outcomes.
Applicant Safety Policy: Fraud and Third-Party Recruiters
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.
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