Data Scientist

Competencies

Bachelor Degree or above in Economics, Finance, Math, Statistics, Actuarial Science, Data Science, Machine Learning Artificial Intelligent or equivalent.

Professional Accreditation : Chartered Banker (added advantage)

No Regulatory or Licensing requirements

Minimum 7 years of experience in analytical and statistical modelling related roles (banking and insurance experience is a plus).

At least 3 years of prior position in a banking role in established financial institutions

Proven track record of successful implementation of ML model and GenAI applications in business processes

Key Responsibilities

Subject matter expert in leveraging advanced analytics, including but not limited to Machine Learning (ML), Natural Language Processing (NLP), Generative AI/BI, and Network Link Analytics, to transform data into actionable insights. This role aims to enhance decision-making and optimize operational efficiencies within the Risk and Control function across the organization, both within Malaysia and regionally.

Identify and socialise use cases with relevant stakeholders, ensuring the alignment to the bank's business objectives and to develop insights for proactive risk identification and controls, risk appetite setting and informed decision making.

Lead and oversee AI initiatives, the development and implementation of forward looking risk management tools, models and/or systems (which include but not limited to ML models, NLP, GenAI/BI) to sharpen risk visibility and enable early detection of complex challenges, improving decision-making agility via automation/data analytics, and hence promote strong risk culture across the bank.

Stay abreast of emerging AI technologies and methodologies, proactively identifying opportunities to embed innovative solutions into risk management practices to maintain competitive advantage.

Oversee and evaluate the performance and assess the effectiveness of deployed AI initiatives to drive iterative improvements and maintain alignment with risk objectives.

Ensure completeness of comprehensive and concise model development documentation, including technical specifications and user guides for each completed use case.

Lead and oversee the user acceptance tests, pilot runs and end-to-end pipeline deployment to ensure the models meet business requirements and are fit for use.

Build strong, collaborative and productive relationships with the various stakeholders. Ensure relationships are strategically forward looking, highly collaborative and productive.

Maintain highest standards of risk management practices with quality and integrity.

This role offers you the opportunity to make a significant impact in the following areas: Enable process improvement, leading to increased efficiency, reduced costs, and enhanced productivity across the organization.

Early detection and prevention of risk within the risk and control function, safeguarding the bank's interests and minimizing potential losses.

Job Specifications

Proficient in SAS Programming *(minimum 5 years)

Proficient Python Programming Language.

Ability to generate analytical insights to business problems.

Present and communicate with clarity on the analytical solutions

Work in Agile Environment

Deep expertise in data mining, analytical techniques and solutions

Hands-on experience in handling and managing large quantum of data via appropriate tools and techniques

Excellent understanding of relevant Big Data tools like SAS, Oracle BDA

Data Modeling experience (e.g. segmentation)

Experience developing and implementing Generative AI/BI models

Experience with RAG, Large Language Models (LLMs), NLP, Machine Learning, Network Link Analytics and the applications. Familiar with cloud-based platforms and services, such as AWS, Azure etc.