Data Scientist

About us:

Skill Quotient Technologies is a global leader in delivering transformative IT solutions, committed to empowering businesses in the digital era since its inception in 2016. Specializing in Cloud Services & Management, Cyber Security, Applications Development, Enterprise Solutions, Process Automation, Data Engineering, Software Testing, Staff Augmentation, and Project and Product Management. Skill Quotient provides cutting-edge services tailored to meet diverse industry needs. Its dedicated cybersecurity division, SecurePlex has achieved prestigious recognition, including being named Cyber Security Company of the Year 2025 by the Malaysia Cyber Security Awards. With a global presence across the USA, Saudi Arabia, Malaysia, Singapore, UAE, and India, Skill Quotient emphasizes quality, security, and innovation, underscored by ISO 27001:2013, CREST, and CMMI-DEV ML 3 certifications.

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 Specification

• 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

Competencies and Skills

• 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