Manufacturing Analytics Scientist - Process Optimization

Hong Kong Unison Limited; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Hong Kong Unison Limited in Singapore is seeking a Data Scientist for manufacturing analytics to drive data-driven improvements across plant operations. You will leverage Seeq, Python, and SQL to develop models and dashboards that reveal actionable insights for engineering and operations teams.

Responsibilities include building data pipelines, deploying predictive models for maintenance and process optimization, and partnering with plant staff to translate real-world problems into scalable

Qualifications

• 6+ years of experience in Data Science / Advanced Analytics.
• Hands-on experience in manufacturing / industrial / plant environments.
• Strong working knowledge of Seeq for time-series analysis, including Seeq Workbench and Data Lab.
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
• Experience building and deploying predictive models for maintenance, process optimization, and quality/yield improvement.

Responsibilities

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities.
• Develop and deploy machine learning models for predictive maintenance and process efficiency improvement.
• Build and maintain data pipelines, analytical datasets, and workflows.
• Present actionable insights through dashboards, reports, and stakeholder discussions.
• Monitor, evaluate, and continuously improve model performance in production.
• Collaborate with plant, engineering, and operations teams to translate business challenges into data science solutions.

Skills

Seeq

Python

SQL

Time-series analytics

Manufacturing analytics

Data visualization

Problem solving

Tools

Seeq Workbench

Seeq Data Lab

Job description

Hong Kong Unison Limited in Singapore is seeking a Data Scientist for manufacturing analytics to drive data-driven improvements across plant operations. You will leverage Seeq, Python, and SQL to develop models and dashboards that reveal actionable insights for engineering and operations teams.

Responsibilities include building data pipelines, deploying predictive models for maintenance and process optimization, and partnering with plant staff to translate real-world problems into scalable