Lead Data Analytics Engineer

Maybank; Kuala Lumpur; On-site; < MYR 1,000; Full time

Benefits offered by this job

Data governance culture

Professional growth in analytics

Job summary

Maybank is seeking a high-impact Leader to design, develop, and deploy advanced analytics solutions that drive business decisions and improve operational efficiency.

You will mentor a team of data scientists, partner with business units, and ensure data governance and risk controls while delivering data-driven insights that enhance customer experience, risk management, and revenue growth.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field.
• Minimum 8–10 years of experience in data science, advanced analytics, or AI/ML roles, with at least 3 years in a leadership capacity.
• Proven track record of delivering analytics-driven business outcomes in financial services or banking.
• Experience in regulated environments with data governance and risk compliance.
• Professional certifications in Data Science or Machine Learning.
• Cloud platform certifications (AWS, Azure, GCP) are advantageous.
• Compliance with internal/regulatory model validation or risk certifications as required.

Responsibilities

• Lead design and deployment of ML and statistical models aligned with business objectives.
• Collaborate with stakeholders to identify problems where data science adds value.
• Oversee full lifecycle of model development from data acquisition to deployment and monitoring.
• Stay updated on AI/ML trends and evaluate new technologies.
• Ensure analytics initiatives comply with data governance and model risk policies.
• Mentor a team of data scientists and analysts; promote continuous learning.
• Coordinate with Data Engineering, IT, and Business teams for seamless integration.
• Apply strong business acumen to translate analytics into strategic insights.

Skills

Leadership

Stakeholder management

Communication

Python

R

SQL

ML frameworks

Big data platforms

Cloud platforms

Agile

Product lifecycle in analytics

Data governance

Education

Bachelor's or Master's in Computer Science/Data Science/Mathematics/Statistics/Engineering

8–10 years in data science/advanced analytics/AI/ML

3+ years in leadership/managerial role

Experience in financial services/banking analytics

Certifications in Data Science or ML

Cloud platform certifications (AWS/Azure/GCP)

Tools

Scikit-learn

TensorFlow

PyTorch

Python

R

SQL

Job description

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.
• 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).