Description
About Mox
Mox is built by and for the ones who aspire to live life to the fullest – we call them Generation Mox! The name Mox reflects the endless opportunities we can create, - Mobile eXperience; Money eXperience; Money X (multiplier), eXponential growth, eXploration… it’s all up for us to define together.
Why Mox
Everything at Mox – from our products, features, to rewards – is designed based on customer research, tailor made for your needs. We care about what customers care about, especially in data security and privacy. Data ethics is core to everyone here at Mox. Mox rewards you with an array of banking and lifestyle benefits. Who says banking can’t be fun?
Who are we looking for?
We are looking for a Analyst / Manager, Risk Analytics and Modelling with a blend of data analytics and science skills as well as risk management expertise to support analytics and modelling initiatives under risk management. We are open to applicants who are not exposed to all the domains requested by this role but willing to explore and develop.
Responsibilities
- Design, build, implement and maintain risk models, e.g. A-score, B-score, Fraud/Mule detection, etc
- Assist ECL and stress test model development and validation
- Operate and govern ECL and stress test models, and explain the model results to stakeholders
- Support the end-to-end model lifecycle, including initiation, data preparation, model development, model validation, model deployment and model monitoring, with MLOps best practice
- Design and build dashboards for risk reporting and analytics
- Define bank-wide risk metrics with risk owners and business owners, and assist the data pipeline development
- Work closely with Risk Owners (e.g. Credit, Fraud, FCC) on data-driven solutions (including but not limited to customer information, digital footprints, credit behavioural data and transaction data) to detect and mitigate credit / fraud / FCC risks, including identifying emerging credit trends and uncovering new fraud, money laundering, and other financial crimes patterns
- Work collaboratively with cross-functional teams and third party on end-to-end data solutions and model development
- Support GenAI initiatives to streamline risk management processes
- Enhance existing analytic techniques by promoting new methodology and best practices in analytics field. Keep up with the state-of-the-art technologies in risk modelling
Requirements
- Bachelor’s degree or higher in Data Science, Computer Science, Mathematics, Statistics, or other quantitative fields. Advanced degree is preferred
- Minimum 3 years of relevant work experience in data and analytics, or risk modelling. Credit/Fraud/FCC risk management and banking experience is an advantage. Candidates with less experience will be considered as Analyst position
- Proficient in programming languages, including SQL and Python
- Familiar with AWS (S3, Athena, SageMaker, Bedrock), Airflow, Tableau and GitHub
- Experience on machine learning, deep learning and GenAI is a plus
- Result oriented, dedicated who can work on own initiative and can deliver on time under pressure with a high level of integrity and flexibility, attention in details and quality standard
- Proficiency in spoken and written English
About Mox Bank
Mox is built by and for the ones who aspire to live life to the fullest – we call them Generation Mox! The name Mox reflects the endless opportunities we can create, - Mobile eXperience; Money eXperience; Money X (multiplier), eXponential growth, eXploration… it’s all up for us to define together.
Why Mox
Mox helps you grow – your money, your world, your possibilities. We equip you with the financial management tools, information and insights you need to make your dreams, big or small, come true. Everything at Mox – from our products, features, to rewards – is designed based on customer research, tailor made for your needs. We care about what customers care about, especially in data security and privacy. Data ethics is core to everyone here at Mox.
Mox rewards you with an array of banking and lifestyle benefits.
All personal data provided by applicants will be used for recruitment and other employment-related purposes only. Personal data of unsuccessful applicants will be erased within 24 months of rejection of the applicant’s application.
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