Data Scientist (Supply Chain)

TL;DR

Data Scientist (Supply Chain): Developing and implementing advanced machine learning models and optimization techniques to drive operational efficiency across manufacturing, procurement, and logistics with an accent on predictive and prescriptive analytics. Focus on building scalable data solutions, creating interactive visualizations, and leading end-to-end data science projects to turn complex insights into actionable business strategies.

Location: Must be based in Singapore (MarinaOne)

Company

A leading global provider of high-quality food and beverage ingredients, sourcing and producing cocoa, coffee, dairy, nuts, and spices across 50 countries.

What you will do

• Analyze large, complex datasets to identify patterns and extract actionable business insights.
• Design and implement machine learning models, including feature engineering, training, and evaluation.
• Develop optimization models using linear and mixed-integer programming to improve supply chain and logistics performance.
• Create interactive dashboards and visualizations using Power BI or Tableau for stakeholders.
• Manage end-to-end data science projects from scoping and resource management to production deployment.
• Maintain and monitor analytical models to ensure ongoing performance and business impact.

Requirements

• Must be based in Singapore
• MS or PhD in Computer Science, Statistics, Operations Research, or a related technical field.
• 5 to 8 years of professional experience in a data science or statistical role.
• Prhirify.globalciency in Python and SQL, with experience in tools like PySpark, Snowflake, and TensorFlow.
• Hands-on experience with simulation and optimization tools such as Gurobi.
• Strong communication skills with the ability to work effectively in cross-functional teams.

Culture & Benefits

• Opportunity to work on global-scale supply chain and sustainability initiatives.
• Collaborative environment focused on innovation and data-driven decision-making.
• Commitment to diversity and equal opportunity employment.
• Engagement with business leadership to drive strategic growth through data science.