Data Scientist

JEET ANALYTICS PTE. LTD.; Singapore; Vor Ort; SGD 90.000 - 140.000; Vollzeit

Zusammenfassung

JEET ANALYTICS PTE. LTD. is seeking a data scientist to analyze manufacturing plant data and drive data-driven improvements. The role focuses on developing and deploying machine learning models using Seeq and Python to optimize predictive maintenance, process efficiency, and quality outcomes.

You will collaborate with cross-functional teams, build data pipelines, ensure data quality, and present actionable insights through dashboards and reports to enable informed decisions.

Qualifikationen

• Experience analyzing manufacturing data to improve operations.
• Proficient in time-series analysis and root-cause investigation.
• Experience deploying ML models in production and monitoring.
• Background in industrial processes and data governance.

Aufgaben

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
• Perform time-series analysis, root cause investigation, and process monitoring using the Seeq platform (Workbench and Data Lab)
• Develop and deploy machine learning models for predictive maintenance, process efficiency improvement, and quality/yield optimization
• Collaborate with plant, engineering, and operations teams to translate business challenges into data science solutions
• Build and maintain data pipelines, analytical datasets, and workflows to support operational analytics
• Monitor, evaluate, and continuously improve model performance in production environments
• Present actionable insights through dashboards, reports, and stakeholder discussions to drive informed decision-making
• Ensure data quality, reliability, and governance across manufacturing data sources
• Promote adoption of data-driven decision-making across plant operations

Kenntnisse

Time-series analysis

Seeq

Python

ML models

Predictive maintenance

Data visualization

Data pipelines

Data governance

Tools

Seeq Data Lab

Azure

AWS

GCP

Jobbeschreibung

Job Summary

Analyze manufacturing plant and process data to deliver data-driven solutions that optimize operations. Develop and deploy machine learning models using Seeq and Python, collaborating with cross-functional teams to improve predictive maintenance, process efficiency, and quality outcomes.

Responsibilities

• Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities
• Perform time-series analysis, root cause investigation, and process monitoring using the Seeq platform (Workbench and Data Lab)
• Develop and deploy machine learning models for predictive maintenance, process efficiency improvement, and quality/yield optimization
• Collaborate with plant, engineering, and operations teams to translate business challenges into data science solutions
• Build and maintain data pipelines, analytical datasets, and workflows to support operational analytics
• Monitor, evaluate, and continuously improve model performance in production environments
• Present actionable insights through dashboards, reports, and stakeholder discussions to drive informed decision-making
• Ensure data quality, reliability, and governance across manufacturing data sources
• Promote adoption of data-driven decision-making across plant operations

Preferred competencies and qualifications

• Experience in industries such as Oil & Gas, Chemicals, and Manufacturing
• Knowledge of MLOps including model deployment, monitoring, and pipeline management
• Exposure to optimization techniques for industrial processes
• Familiarity with cloud platforms such as Azure, AWS, or GCP
• Experience with data visualization tools, real-time/streaming data analytics, and data engineering (ETL, data pipelines, data lakes)