Company

Airwallex

Released at

2023-Mar-13

Close at

2023-Jul-27

Job Type

FULLTIME

Salary

SGD 20000 per MONTH

Location

Singapore, , Singapore

Company Description

The world as we know it is no longer the same. Changes now occur in days and months, not years. The digital revolution is here, and Airwallex is at the centre, facilitating the transformation of businesses from offline to online, from local to global.Airwallex was built with a single purpose in mind – to create a world where all businesses can operate without borders and restrictions, and by doing so, propel the growth of the global digital economy.

Job Description

    1. Work with risk stakeholders throughout the company to identify opportunities for leveraging company data to drive risk solutions.
    2. Mine and analyze data from the company database to drive optimization and improvement of risk strategies. 
    3. Assess the effectiveness and accuracy of new risk data sources and data gathering techniques. 
    4. Develop customized data models and algorithms to risk data sets and communicate the insights of the models to related stakeholders.  
    5. Develop A/B testing framework and test model quality for risk product. 
    6. Coordinate with multiple functional teams to implement models and monitor performance.
    7. Develop processes and tools to monitor and analyze model performance and data accuracy. 

Requirements

    1. Bachelor's degree or higher in Computer Science, Math & Statistics, Finance & Economics, Engineering or related data disciplines.
    2. At least 7 years of experience as a data analyst, data scientist or data engineer.
    3. Strong problem-solving skills with an emphasis on risk-related product development.
    4. Hands-on and solid experiences in using statistical computer languages (Python, R, SQL, etc.) to manipulate data and draw insights from large data sets.
    5. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks.
    6. Knowledge of advanced statistical techniques and concepts (regression, simulation, properties of distributions, statistical tests, etc.) and experience with applications.
    7. A drive to learn and master new technologies and techniques.
    8. Excellent written and verbal communication skills in English for coordinating across teams.
    9. Experience working on data-driven financial risk models (e.g., money-laundering risk, credit risk, fraud risk) is preferred.
    10. Experience running data analytics under cloud environments and using web applications is preferred. 

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