Assistant Director,Risk Modeling and Monitoring
2 days ago
- Have fundamental understanding of ML models (Boosting, Random Forests, Deep Learning, Anomaly Detection, Unstructured Data Analysis) and all major Statistical algorithms used in Credit Scoring and Strategy. Experience in other AI applications would be added advantage.
- Partner with functional business leaders in owning & developing data science applications for higher business value.
- Translate key analytical solutions as generic and re-deployable across regions / markets
- Can see the 'bigger picture' and assess relationship between recommended solutions and business performance
- Own delivery of high quality data science solutions for the business stakeholders across geographies.
- Functionally oversee a cross functional team of consultants, in an Agile working environment for rapid prototyping, developing and implementing data science led applications / services.
- This role in an Individual contributor role that requires strong functional contribution in the Advanced Analytics space.
- Ensure that the solutions adhere to HSBC risk policies and governance.
- Work on multiple projects simultaneously and deliver in a timely, efficient and effective manner.
- Provide support in recruitment, on-boarding, training, coaching and developing talent.
- Ensure adherence with all the applicable compliance policies (Data security policy, AML, operational risk, Functional manual, Group Compliance Manual, Audit recommendations, Internal Control requirements, regulatory guidelines etc.) and business standards of Organization as applicable. Take timely action on Audit comments and be able to demonstrate compliance with Internal controls
- 10+ years of experience using statistical concepts & machine learning models to solve complex business problems or 18+ months in a GCB 5 role in a similar domain in HSBC.
- PH.Ds / Master's degree in Mathematics, Statistics/Econometrics or Bachelors in Engineering, Computer Science other quantitative fields of study.
- Have fundamental experience in major algorithms widely used in credit scoring and credit strategy like traditional scorecards and decision trees (multiple algorithms in both cases).
- Strong developer (beyond beginner or intermediate) level skills in both Python and R with deeper expertise in at least one is necessary for this role. Open-source libraries in other languages like Java would be an added advantage.
- Experience in developing data science applications leveraging open source.
- Knowledge and exposure to cloud analytics platform such as GCP would be a help.
- Previous experience in a ML or data scientist role and a track record of building and implementing ML or AI models in different platforms
- Collaborate with partners across business groups, evaluate emerging techniques that may contribute to existing data science capabilities and computational models
- Strong foundation in retail credit risk with out-of-the box thinking to drive improved business performance
- Strong stakeholder management skills and seamless delivery of data science initiatives across markets
- Excellent written and verbal communication skills. Ability to develop and effectively communicate complex concepts and ideas
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