Data Scientist - Manufacturing Analytics

Unison Group; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Unison Group is seeking a senior data scientist to analyze manufacturing plant and process data, performing time-series analytics with Seeq and building predictive models for maintenance and process efficiency. You will collaborate with plant and engineering teams to translate operational challenges into scalable data solutions.

The role requires hands-on Seeq experience, Python and SQL proficiency, and a strong ability for root-cause analysis and data-driven decision support within an

Qualifications

• 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

Responsibilities

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities.
• Use Seeq platform for time-series analysis, root cause investigation, process monitoring and visualization.
• Develop and deploy machine learning models for predictive maintenance, process efficiency improvement, and 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.

Skills

Time-series analytics

Predictive modeling

Anomaly detection

Pandas/NumPy/Scikit-learn

SQL proficiency

Seeq

Manufacturing exposure

Root-cause analysis

Data science

Tools

Seeq Workbench

Seeq Data Lab

Python

SQL

Job description

Must-Have Skills / Requirements

• 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)

Roles & Responsibilities

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
• Use Seeq platform for:
• Time-series analysis
• Root cause investigation
• 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