Data Scientist (Up to 16k)

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

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.

experience

4 years

skills

Python, SQL, Tensorflow, Pytorch

qualifications

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.

education

Bachelor Degree