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Senior Data Scientist, Credit Risk, Digibank
2 weeks ago
Job Description:
We are living in dynamic times. Technology is reshaping how we live, and we want to use it to redefine how financial services are offered. Digibank is a Grab-Singtel consortium, aimed at enabling the underserved groups to easily access transparent financial services that are embedded in their everyday activities, helping them achieve a better quality of life. We are incredibly excited to build a Digital Bank with the right foundation using data, technology and trust to solve problems and serve customers
Role:
- Develop and create predictive models associated with credit scoring, fraud detection and prediction of suspicious activity.
- Advise in underwriting decisions, in partnership with Credit Risk team, and proactively monitor credit performance to identify targeted areas for improvement.
- Identify, collect and process data required to support statistical analysis and decision making for risk
- Work closely with Lending and Credit Risk teams to translate and calibrate requirements into developing and optimising appropriate models.
- Understand the expectations of the model governance team, the business and the regulators.
- Leverage on alternative data sources to augment underwriting and credit risk models.
- Design and implement performance reports and dashboards to communicate actionable insights to stakeholders
Must Haves:
- Phd’s/Master’s/Bachelor’s degree, preferably in Statistics, Mathematics, Economics, Finance, Risk Management, or relevant background.
- Experience in building risk models (ideally PD, EAD/LGD, IFRS9) for retail customers across different countries, particularly Singapore.
- Experience in working across risk management across the full spectrum of customer journey from underwriting, onboarding, customer management, within a fintech or risk environment.
- Has domain knowledge in retail credit products, banking and regulations (Basel, IFRS).
- Extensive hands-on experience with tools such as Python, R, Presto, SQL/Hive, and Data Visualization platforms like Tableau/ Power BI/D3.js
- Technical expertise in data retrieval, data models, data mining and predictive modeling.
- Proficient with machine learning techniques and statistical classification/regression for credit risk modelling.
- Results and detail-oriented, with strong intuitions on how to solve problems creatively and quickly and thrives in a dynamic working environment.
