Data Scientist - Manufacturing Analytics

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

Data Scientist - Manufacturing Analytics

• 6+ years of experience in Data Science / Advanced Analytics
• Hands-on experience in manufacturing / industrial / plant environments
• Strong working knowledge of Seeq (industrial analytics platform) for time-series analysis, including both Seeq Workbench and Data Lab (using the seeq spy library).
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL
• Strong understanding of:
• Machine Learning (regression, anomaly detection, predictive models)
• Statistical modeling and hypothesis-driven analysis
• Time-series / sensor data analytics
• Experience building and deploying predictive models for:
• Predictive maintenance
• Process optimization
• Quality and yield improvement
• Ability to work with sensor data, process data, and operational datasets
• Strong analytical thinking, troubleshooting, and root-cause analysis capability

Good-to-Have Skills

• Experience in industries such as:
• Oil & Gas, Chemicals, Manufacturing
• Knowledge of MLOps (model deployment, monitoring, pipelines)
• Exposure to optimization techniques for industrial processes
• Exposure to cloud platforms (Azure / AWS / GCP)
• Familiarity with data visualization tools, real-time / streaming data analytics, data engineering (ETL / data pipelines / data lakes)
• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
• Time-series analysis
• Process monitoring and visualization
• Develop and deploy machine learning models for:
• Predictive maintenance
• Process efficiency improvement
• Quality / yield optimization
• Work closely with plant, engineering, and operations teams to understand real-world process issues
• Translate business and operational challenges into data science solutions
• Build and maintain data pipelines, analytical datasets, and workflows
• Monitor, evaluate, and continuously improve model performance in production
• Present actionable insights through dashboards, reports, and stakeholder discussions
• Ensure data quality, reliability, and governance across manufacturing data sources
• Drive adoption of data-driven decision-making across plant operations