全职 Senior Data Analytics Engineer 工作, 薪水, Maybank Federal Territory 公司招聘中 - Ricebowl

Job Purpose

Responsible for leading the design, development, and deployment of advanced analytics solutions that drive business decision-making and operational efficiency across the bank. This role collaborates with business units, data scientists, and technology teams to translate business challenges into data-driven solutions, ensuring alignment with the bank’s digital and data transformation strategy. The role supports the bank by leveraging data to generate actionable insights that contribute to improved customer experience, risk management, and revenue growth.

Key Accountabilities & Outcome

• Lead the design and implementation of machine learning and statistical models aligned with business objectives.
• Partner with stakeholders to identify business problems where data science can add value.
• Oversee full lifecycle of model development, from data acquisition and feature engineering to deployment and monitoring.
• Stay abreast of emerging AI/ML trends and technologies; evaluate and introduce suitable innovations.
• Ensure all analytics initiatives adhere to data governance, privacy, and model risk management policies.
• Lead and mentor a team of data scientists and analysts; foster a culture of continuous learning.
• Work closely with Data Engineering, IT, and Business teams to ensure seamless integration of analytics solutions.

Required Skills & Competencies

• Strong proficiency in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) and data analytics tools (e.g., Python, R, SQL).
• Deep understanding of big data platforms and cloud-based data ecosystems (e.g., Hadoop, Spark, Databricks, Azure/GCP/AWS).
• Excellent business acumen with ability to translate analytics into strategic insights.
• Strong leadership, stakeholder management, and communication skills.
• Familiarity with data privacy, model governance, and ethical AI principles.
• Agile delivery methodologies and experience with product lifecycle management in analytics projects.

Education / Qualification

• Bachelor's or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field
• Minimum of 8–10 years of experience in data science, advanced analytics, or AI/ML roles, with at least 3 years in a leadership or managerial capacity.
• Proven track record of delivering analytics-driven business outcomes in financial services or banking industry.
• Experience working in a regulated environment with exposure to data governance and risk compliance.
• Professional certifications in Data Science or Machine Learning
• Certification in cloud platforms (AWS, Azure, GCP) is advantageous.
• Compliance with any internal/regulatory model validation or risk certifications (where required by local regulation or internal governance).