Our Client operates in the Financial Services Industry, with its headquarters rooted strongly in Singapore. It has its branches spread to more than 15 countries, providing employment to more than 25,000 people all over the world. They fall in the Forbes Global 2000 (2022). Their core business is to offer financial services to its clients, ranging from Investment Banking to Corporate as well as Personal Banking Services.. They are also well known for their Residential Home Loan Business.
Responsibilities:
Responsible for building our client’s AFC analytical capabilities in response to external and internal requests; developing, maintaining, and upgrading in-house AFC analytical models when needed
Support model maintenance:
- Liaise with Business Analyst to receive and understand business feedback on model performance and incorporate feedback into models
- Re-train and recalibrate existing AFC analytical models to prevent model drift periodically or as needed
New model development:
- Work closely with model end-users and other key stakeholders (e.g., Head of Modelling, Business Analyst, Data and Ops Engineer, GC) to identify additional areas which require analytics support or future model build and include those models in development pipeline
- Develop model narratives (e.g., purpose, logic, parameters, data requirements, output surfacing / structuring) in collaboration with the business and other relevant stakeholders
- Work closely with other Data Scientist(s) and Business Analyst, and undertake the end-to-end AFC model development, including data wrangling, exploratory data analysis, feature selection, model selection, training, testing, etc.
- Build a range of models (rule-based, supervised / unsupervised models, etc.) on structured, semi-structured, and/or unstructured data if needed
Special projects:
- Support special / high-priority projects, including building AFC analytical capabilities in response to external (e.g., regulatory) requests or internal intelligence, or based on gaps identified for existing analytical capabilities / models
- Keep abreast with the latest, cutting-edge developments in data science and advanced analytics and recommend adoption of best practices within the bank, in relation to AFC / AML
- Communicate with Business Analyst to understand new regulatory requirements / policy updates relating to the areas / risks covered by the AFC analytical models and work with the relevant teams to ensure that these updates are appropriately reflected in those models
Model governance:
- Support the Head of Modelling in identifying enhancements to existing model governance policies and processes, particularly in relation to newly built models
- Participate in the model governance process, including but not limited to model testing, assessing models for biases and for compliance with applicable ethics standards
Requirements:
- 5 –10 years of experience working in the technology space and preferably 2 –4 years of data science / data analytics experience
- 1 –2 years of experience working with advanced analytical models/tools/applications (e.g., machine learning)
- Prior experience working on large-scale analytics projects
- Experience in or familiarity with analytics related to AML/AFC/compliance risks
- Ability to clearly communicate technical results in an easy-to-understand mannerand tailoring them to different audiences
- Ability to handle multiple priorities and work under pressure
- Bachelor’s degree, or equivalent, in Computer Science, Engineering, Statistics, Mathematics, Business Analytics etc.
Technical skills:
- R and Python for data science, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
Other details:
- This is an Individual contributor role.
- Candidate must have strong experience in Data Analytics – Big Data, Hadoop etc.
- Would be responsible for developing and designing the model from scratch.
- AML, AFC experience preferred, not a must have.
- Other non-banking industries can be looked at provided strong technical background.