Data Scientist: Predictive ML & Data-Driven Insights for Impact

Tokio Marine Insurans (Malaysia) Berhad; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Tokio Marine Insurans (Malaysia) Berhad is seeking a Data Scientist to develop and deploy data-driven solutions using statistics, predictive modelling and machine learning. You will transform complex data into actionable insights to support business decisions and improve performance across functions.

Responsibilities include exploring large datasets, building and monitoring models, deploying analytics solutions, and presenting findings to both technical and non-technical stakeholders.

Qualifications

• Degree in data science, statistics, actuarial science, CS, or math.
• 3–4 years in data science, analytics or modelling.
• Strong stats, modelling and ML knowledge.
• Proficient with Python or R and SQL; handling large datasets.
• Experience with model development, validation and production deployment.

Responsibilities

• Perform exploratory and advanced data analysis on large datasets to identify trends and opportunities.
• Design, validate and monitor predictive and ML models to meet business needs.
• Support deployment and monitoring of models for accuracy and reliability.
• Collaborate with business units to translate requirements into analytics solutions.
• Prepare and analyse data from multiple sources to support modelling initiatives.
• Present findings to technical and non-technical stakeholders.
• Maintain model documentation and governance standards.

Skills

Statistical knowledge

Predictive modelling

Machine learning

Python/R

SQL

Model deployment

Analytical thinking

Communication

Education

Bachelor's degree in Data Science/Statistics/CS

Tools

Tableau

Power BI

Job description

Tokio Marine Insurans (Malaysia) Berhad is seeking a Data Scientist to develop and deploy data-driven solutions using statistics, predictive modelling and machine learning. You will transform complex data into actionable insights to support business decisions and improve performance across functions.

Responsibilities include exploring large datasets, building and monitoring models, deploying analytics solutions, and presenting findings to both technical and non-technical stakeholders.