Data Scientist II — AI Analytics & ML for Scale

WD; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

WD is building the infrastructure behind the AI-driven data economy. Our Data Science team within Operations develops analytics and ML solutions to solve complex business problems, taking ideas from concept through data prep, model building, and system integration.

You will work hands-on across analytics and ML model development using Python, SQL, Linux, Docker, and BI tools like Tableau and Power BI, delivering end-to-end solutions that power enterprise infrastructure and hyperscale data

Qualifications

• Master's degree in Data Science, AI, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Fresh graduates are welcome to apply.
• Proficiency in Python and SQL for data manipulation, pipeline development, and model implementation.
• Hands-on experience with machine learning algorithms spanning regression, classification, clustering, and deep learning methods.
• Familiarity with software development tools and environments including version control, Linux-based systems, and containerization tools.
• Experience building data visualizations or dashboards using enterprise BI tools (e.g., Tableau or Power BI)

Responsibilities

• Automate data extraction, cleaning, processing, feature engineering, and exploratory analysis using Python, R, and SQL across structured and unstructured operational datasets.
• Develop advanced machine learning and deep learning models to support operational excellence, predict outcomes of interest, and identify patterns across enterprise datasets
• Build and deploy end-to-end analytics applications, covering data preparation, model development, and system integration
• Visualize analytical findings and model outputs using enterprise BI tools such as Tableau, Power BI, or similar platforms to create intelligent dashboards that support operational decision-making.
• Validate and monitor deployed models in production, tracking performance drift and retraining as needed to maintain accuracy and reliability.
• Document model methodologies, data pipelines, and application architecture using version-controlled repositories to support reproducibility and team collaboration.
• Translate analytical findings into clear, actionable insights and present results to engineering and operations partners across functions.
• Leverage AI-assisted tools to accelerate workflows, while critically evaluating outputs before use.

Skills

Python

SQL

Data science

Machine learning

Deep learning

Tableau

Power BI

Linux

Docker

Version control

Education

Master's degree

Tools

GitHub

Job description

WD is building the infrastructure behind the AI-driven data economy. Our Data Science team within Operations develops analytics and ML solutions to solve complex business problems, taking ideas from concept through data prep, model building, and system integration.

You will work hands-on across analytics and ML model development using Python, SQL, Linux, Docker, and BI tools like Tableau and Power BI, delivering end-to-end solutions that power enterprise infrastructure and hyperscale data