jobs in Unison Group

全职 Data Scientist - Manufacturing Analytics Jobs, in Unison Group - Ricebowl

Data Scientist - Manufacturing Analytics

Unison Group

Undisclosed

全职

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

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

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