Senior Executive, Data Analytics Engineer

Maybank; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

Maybank in Kuala Lumpur is seeking an senior data science professional to design, develop and deploy advanced analytics solutions that drive business decisions and operational efficiency. You will collaborate with business units, data scientists and tech teams to translate challenges into data-driven solutions aligned with the bank's data strategy.

Responsibilities include end-to-end model lifecycle, staying ahead of AI/ML trends, and ensuring compliance with governance, privacy and risk

Qualifications

• Bachelor's or Master’s degree in CS/DS/Math/Stats/Engineering.
• 6–10 years in data science, analytics, or AI/ML roles.
• Track record delivering analytics-driven outcomes in financial services.
• Experience in regulated environments with data governance and risk compliance.
• Certifications in Data Science or ML.
• Cloud platform certifications (AWS/Azure/GCP) are advantageous.
• Compliance with model validation and risk certifications where required.

Responsibilities

• Design and implementation of ML and statistical models aligned with business objectives.
• Partner with stakeholders to identify business problems where data science adds 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.
• 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 (Python, R, SQL).
• Deep understanding of big data platforms and cloud-based data ecosystems (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.

Skills

Python

R

SQL

Scikit-learn

TensorFlow

PyTorch

Big data

Leadership

Stakeholder management

Communication

Education

BSc/ MSc

Data Science cert

Cloud certs

Banking/reg compliance

Tools

Hadoop

Spark

Databricks

AWS

Azure

GCP

Job description

Responsible for 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

• In charge of designing 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.
• 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 6–10 years of experience in data science, advanced analytics, or AI/ML roles
• 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).