Quality Control jobs in Malaysia
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Principal Data Scientist
Job summary
A major financial institution is looking for an experienced AI/ML Lead to drive scalable model development and improve the operationalization of ML processes. Candidates should have a Master's or PhD and a solid background in IT analytics, with at least 10-15 years of experience. This role involves mentoring data scientists, optimizing MLOps practices, and ensuring governance and compliance in model deployment. Exceptional analytical skills are crucial for influencing strategic decisions within the organization.
Qualifications
- Strong academic qualifications with advanced degrees in quantitative fields.
- Minimum of 10-15 years of experience in IT analytics infrastructure.
- Expertise in business intelligence and application design.
Responsibilities
- Lead scalable AI/ML model development with MLOps for deployment.
- Translate business challenges into structured data initiatives.
- Mentor data scientists in ML methods and MLOps practices.
Skills
Education
- Lead scalable AI/ML model development with MLOps for deployment, monitoring, and continuous improvement.
- Translate business challenges into structured data initiatives using reproducible, traceable MLOps practices.
- Drive innovation with advanced AI, ML, and MLOps techniques like CI/CD and containerization.
- Ensure MLOps‑compliant models with governance, ethical standards, versioning, monitoring, and regulatory compliance.
- Mentor data scientists in ML methods and MLOps practices, improving operationalization and technical excellence.
- Collaborate with engineering teams to optimize pipelines, orchestration, and feature stores for production data.
- Monitor and optimize models through automated pipelines, drift detection, retraining, and continuous performance tracking.
- Partner across departments embedding AI/ML workflows, supported by MLOps for efficient integration.
- Communicate analytical results and provide MLOps dashboards, ensuring clarity and influencing strategic decisions.
- Automate AI/ML lifecycle stages—training, validation, deployment, monitoring—using MLOps to streamline and scale operations.
Strong academic qualifications, with an advanced degree (Masters or PhD) in a quantitative discipline (typically information technology, computer systems, or mathematics) and advanced software certifications will be an added advantage.
Minimum 10‑15 years with:
- Extensive experience in information technology analytics infrastructure, business systems analysis, business intelligence, application design, development, testing/software QA, implementation, coding, data modeling and reporting.
- Broad based experience with rapid prototyping & production implementation on large datasets (terabytes/petabytes), being aware of efficient algorithmic design, memory and CPU usage/ scalability.
- In‑depth experience developing advanced models impacting business & derived from business analytics utilizing the landscape of structured, unstructured data, transactional data, text and speech analytics.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.