data scientist (up to 16k).

About the company

The client is a leading life insurer in Malaysia going through a Digital Transformation. They need a highly skilled Data Scientist to join their team to build traditional ML models to improve insurance day to day business operations.

Key Responsibilities

• End-to-End Model Development: Design, build, evaluate, and deploy predictive models using supervised and unsupervised learning techniques.
• Predictive & Time Series Modeling: Develop time series forecasting and regression models to predict business outcomes, trends, and demand patterns.
• Anomaly Detection & Classification: Build algorithms to detect operational anomalies, fraud, or system outliers while refining classification workflows.
• Pipeline & Feature Engineering: Write clean, modular Python and SQL scripts to clean, transform, and extract high-value features from complex structured and unstructured datasets.
• Framework Implementation: Leverage TensorFlow, PyTorch, and XGBoost to train, tune, and optimize machine learning and deep learning models for production readiness.
• Stakeholder Collaboration: Translate complex business questions into quantitative frameworks and present analytical findings directly to technical leads and executive business stakeholders.

Qualifications

• 4+ years of professional experience in a Data Scientist role, delivering end-to-end machine learning solutions in production environments.
• Strong business acumen with a proven track record of translating business requirements into technical data science problems.
• Solid background in model evaluation, hyperparameter tuning, and model lifecycle management.

Key Skills Required

• Core Machine Learning: Predictive Analytics, Regression, Time Series Analysis, Classification, Supervised & Unsupervised Learning, Anomaly Detection.
• Frameworks & Libraries: TensorFlow, PyTorch, XGBoost, Scikit-Learn.
• Programming & Database: Advanced proficiency in Python and SQL.