Data Scientist – End-to-End ML for Insurance Ops

Randstad Malaysia; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Randstad Malaysia in Kuala Lumpur is seeking an experienced Data Scientist to design, build, and deploy predictive models to improve insurance operations. You will develop time series forecasts, detect anomalies, and create robust feature pipelines using Python and SQL.

The role requires 4+ years of production ML experience, strong business sense, and proficiency with TensorFlow, PyTorch, XGBoost, and Scikit-Learn. Collaboration with executives and technical leads is essential.

Qualifications

• 4+ years of professional experience delivering end-to-end machine learning solutions in production.
• Strong business acumen with ability to translate business requirements into data science problems.
• Solid background in model evaluation, hyperparameter tuning, and model lifecycle management.

Responsibilities

• End-to-End model development: design, build, evaluate, and deploy predictive models.
• Predictive & Time Series Modeling: develop time series forecasting and regression models.
• Anomaly Detection & Classification: build algorithms to detect anomalies and refine classification workflows.
• Pipeline & Feature Engineering: write clean Python and SQL to extract high-value features.

Skills

Predictive Analytics

Time Series Analysis

Regression

Classification

Unsupervised Learning

Anomaly Detection

Education

Bachelor’s or Master’s degree in Data Science/CS/Statistics/Applied Mathematics

Tools

TensorFlow

PyTorch

XGBoost

Scikit-Learn

Job description

Randstad Malaysia in Kuala Lumpur is seeking an experienced Data Scientist to design, build, and deploy predictive models to improve insurance operations. You will develop time series forecasts, detect anomalies, and create robust feature pipelines using Python and SQL.

The role requires 4+ years of production ML experience, strong business sense, and proficiency with TensorFlow, PyTorch, XGBoost, and Scikit-Learn. Collaboration with executives and technical leads is essential.