Lead Data Specialist

Worldline; Kuala Lumpur; Hybrid; MYR 100,000 - 150,000; Full time

Job summary

A global technology leader in Malaysia is seeking a Lead Data Specialist to spearhead advanced analytics and AI initiatives. The role involves leading machine-learning projects, mentoring engineers, and collaborating across teams to drive innovation. The ideal candidate should have a strong background in data engineering, extensive experience with big data analytics, ETL processes, and cloud platforms, alongside excellent communication skills. This position offers a hybrid working model and comprehensive benefits.

Benefits

Flexible benefits

Special birthday leave

Hybrid working model

Comprehensive health insurance coverage

Professional development opportunities

Global exposure working with teams across regions

Qualifications

• 10+ years of experience in data science, big data analytics, implementation, and real-time/batch data jobs.
• Extensive experience with ETL tools and processes.
• Strong understanding of relational and non-relational databases.

Responsibilities

• Lead the full lifecycle of machine-learning projects from ideation through deployment.
• Mentor and guide other engineers and future developers.
• Collaborate with business teams to identify opportunities for AI integration.

Skills

Data science

Machine learning

Data engineering

Cloud platforms (AWS, Azure, Google Cloud)

Python

Big data analytics

ETL tools

Data governance

Communication skills

Data visualization tools

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field

Tools

Airflow

Informatica

Kafka

Terraform

Tableau

Job description

Worldline helps businesses of all shapes and sizes to accelerate their growth journey - quickly, simply, and securely. We are the innovators at the heart of the payments technology industry, shaping how the world pays and gets paid. Our technology powers the growth of millions of businesses across five continents and accelerates careers of our people.

The Opportunity

We are seeking a Lead Data Specialist with a strong hands‑on background in data engineering to spearhead advanced analytics and AI initiatives. This pivotal leadership role involves building sophisticated machine‑learning models, shaping the data landscape, and bridging data science/engineering with business‑facing AI.

Day‑to‑Day Responsibilities

• Contribute within a team of AI leads, executing the data science roadmap to deliver hyper‑personalized customer experiences.
• Lead the full lifecycle of machine‑learning projects—from ideation through deployment, monitoring, and iteration.
• Mentor and guide other engineers and future developers, establishing best practices for modeling, code quality, and project execution.
• Advanced Modeling & Analytics
  • Develop and implement a range of machine‑learning models (recommendation engines, customer segmentation, propensity models, transaction fraud detection).
  • Perform exploratory data analysis to identify key patterns and features that drive business value.
  • Translate complex business challenges into precise data‑science problems and deliver scalable, statistically robust solutions.
• Design, develop, and maintain scalable, high‑performance data pipelines and ETL processes to ingest, process, and transform large data sets from various sources.
• Collaborate with LLM engineers to understand their data requirements and provide efficient data solutions.
• Work with AI engineers, product developers, and network engineer to deliver end‑to‑end AI projects.
• Collaborate with product, engineering, and business teams to identify opportunities for AI integration and innovation.
• Data Infrastructure, Data Lakehouse & Deployment
  • Support scalable AI infrastructure and optimize resource utilization.
  • Conduct capacity planning for AI and data analytics workloads, on‑premise and cloud.
  • Architect and implement cloud‑based data solutions using AWS (S3, Redshift, Glue), Azure (Data Lake, Synapse) or Google Cloud (BigQuery, Dataflow).
  • Work with big data technologies (Hadoop, Spark, Kafka, NoSQL such as MongoDB) to handle large‑scale processing.
  • Support optimization of AI and data pipeline workloads with CI/CD, model versioning, monitoring, drift detection.
  • Implement APIs and microservices for seamless integration into enterprise applications.
  • Ensure infrastructure aligns with security, compliance, and regulatory requirements (PCI‑DSS, GDPR).
  • Familiarity with IBM i and z, especially managing datalake and deploying datawarehouses.
• Data Quality, Governance & Automation
  • Ensure data quality, integrity, and security with governance policies.
  • Optimize ETL/ELT jobs for performance and scalability.
  • Monitor, evaluate, and optimize pipelines for continuous improvement.
  • Implement data quality checks, validation processes, monitoring, and alerting systems.
  • Establish processes for deploying, monitoring, and maintaining machine‑learning models in production.
• Technology & Innovation
  • Mentor junior data scientists and engineers.
  • Collaborate with AI engineers, business analysts, and stakeholders to deliver solutions that meet business objectives.
  • Stay updated with industry trends and emerging technologies.

What are we looking for

• Qualifications & Skills
  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
  • 10+ years of experience in data science, big data analytics, implementation, and real‑time/batch data jobs.
  • Extensive experience with ETL tools and processes (e.g., Airflow, Talend, Informatica).
  • Proficiency in Python, Java, or Scala.
  • Hands‑on experience with cloud platforms (AWS, Azure, or Google Cloud) and their data services.
  • Strong understanding of relational (PostgreSQL, MySQL, Db2) and non‑relational (MongoDB, DynamoDB) databases.
  • Experience with infrastructure‑as‑code tools such as Terraform.
  • Experience with stream processing technologies (Kafka, Kinesis).
  • Experience with data visualization tools (Tableau, Power BI).
  • Experience with machine‑learning frameworks (TensorFlow, PyTorch) required.
  • Experience with data modeling, warehousing, lakehouse, and governance.
  • Excellent problem‑solving skills.
  • Strong communication skills and ability to convey complex technical concepts to non‑technical stakeholders.
  • Knowledge of regulatory and compliance standards in the payments industry (PCI‑DSS, GDPR).

Perks & Benefits

• Flexible benefits (applicable for Malaysia only)
• Special birthday leave
• Hybrid working model with flexibility
• Comprehensive health insurance coverage
• Professional development and training opportunities
• Global exposure working with teams across regions

Shape the evolution

Join a global team of over 18,000 innovators across 40+ countries; accelerate your career and make an impact on society while pursuing your ambitions.

Learn more about life at Worldline at jobs.worldline.com