PTS Advance
The
Data Insights Analyst
transforms refinery operational data into actionable insights, and works with stakeholders to proactively resolve risks.
This role focuses on monitoring and analyzing data from multiple sources like
PI ,
SAP ,
PCMS , wireless sensors, and other in order to identify
trends, anomalies, and potential risks . The analyst collaborates with subject matter experts (SMEs) and stakeholders across refineries to ensure timely communication and resolution of issues that impact
safety, reliability, and performance .
Job Responsibilities:
Data Monitoring & Analysis
Review dashboards, alerts, and reports from different systems and data sources like PI, SAP, PCMS, and other data sources. Automate the alerts, dashboards, or reports where possible.
Employ analytics, trending, and pattern recognition techniques to detect anomalies, deviations, or early failure indicators on processing equipment.
Perform root-cause analysis and validate findings using historical and real-time data.
Flag operational risks and elevate critical issues through established workflows.
In the near future work with AI models to aid in data analysis and anomaly detection.
Highlight potential risks related to asset health, process safety, and operational efficiency.
Create clear reports, dashboards, and visualizations for non-technical stakeholders.
Support development of alerts and KPIs for proactive decision-making.
Collaborate with data engineers and platform teams to improve data quality and availability.
Partner with other teams such as operations, reliability, maintenance, and process engineering teams to interpret insights and validate risks.
Document findings and recommendations.
Recommend improvements in data collection, monitoring strategy, and predictive maintenance programs.
Success Metrics
Reduction in unplanned downtime and PSM incidents.
Improved anomaly detection accuracy and response time.
Effective communication and stakeholder engagement.
Supporting the Drone Program (an option)
Conduct remote visual inspections using the drones in the refineries.
Required Qualifications – Education, Skills & Experience:
Bachelor’s degree in Chemical or Process or Mechanical Engineering.
A least 5 years work experience in Industrial Processing Plant (Oil & Gas refinery preferred), where understanding of how different process variables and different processing equipment interact with each other is a key element of your role.
Proven ability to interpret complex datasets from multiple sources and identify patterns or correlations leading to predictive insights. Can use varoius statistical anlaysis methods such as Analysis of Variance (ANOVA) and Regression Analysis.
Excellent communication skills for translating technical insights into business language and for communication with the stakeholders.
Tools & Platforms
Familiarity with PI System (OSIsoft), SAP, PCMS, wireless sensor and other platforms as applicable where raw data are collected.
Proficiency in Power BI, Excel, and basic scripting (SQL/Python a plus).
Collaboration tools (Teams, ServiceNow).
Preferred Qualifications
Familiarity with AI models and using AI to aid data analysis and anomaly detection.
Part 107 license to fly a drone is an advantage.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Analyst
Industries
Chemical Manufacturing and Oil and Gas
Inferred from the description for this job
Medical insurance
Vision insurance
401(k)
#J-18808-Ljbffr
Data Insights Analyst
transforms refinery operational data into actionable insights, and works with stakeholders to proactively resolve risks.
This role focuses on monitoring and analyzing data from multiple sources like
PI ,
SAP ,
PCMS , wireless sensors, and other in order to identify
trends, anomalies, and potential risks . The analyst collaborates with subject matter experts (SMEs) and stakeholders across refineries to ensure timely communication and resolution of issues that impact
safety, reliability, and performance .
Job Responsibilities:
Data Monitoring & Analysis
Review dashboards, alerts, and reports from different systems and data sources like PI, SAP, PCMS, and other data sources. Automate the alerts, dashboards, or reports where possible.
Employ analytics, trending, and pattern recognition techniques to detect anomalies, deviations, or early failure indicators on processing equipment.
Perform root-cause analysis and validate findings using historical and real-time data.
Flag operational risks and elevate critical issues through established workflows.
In the near future work with AI models to aid in data analysis and anomaly detection.
Highlight potential risks related to asset health, process safety, and operational efficiency.
Create clear reports, dashboards, and visualizations for non-technical stakeholders.
Support development of alerts and KPIs for proactive decision-making.
Collaborate with data engineers and platform teams to improve data quality and availability.
Partner with other teams such as operations, reliability, maintenance, and process engineering teams to interpret insights and validate risks.
Document findings and recommendations.
Recommend improvements in data collection, monitoring strategy, and predictive maintenance programs.
Success Metrics
Reduction in unplanned downtime and PSM incidents.
Improved anomaly detection accuracy and response time.
Effective communication and stakeholder engagement.
Supporting the Drone Program (an option)
Conduct remote visual inspections using the drones in the refineries.
Required Qualifications – Education, Skills & Experience:
Bachelor’s degree in Chemical or Process or Mechanical Engineering.
A least 5 years work experience in Industrial Processing Plant (Oil & Gas refinery preferred), where understanding of how different process variables and different processing equipment interact with each other is a key element of your role.
Proven ability to interpret complex datasets from multiple sources and identify patterns or correlations leading to predictive insights. Can use varoius statistical anlaysis methods such as Analysis of Variance (ANOVA) and Regression Analysis.
Excellent communication skills for translating technical insights into business language and for communication with the stakeholders.
Tools & Platforms
Familiarity with PI System (OSIsoft), SAP, PCMS, wireless sensor and other platforms as applicable where raw data are collected.
Proficiency in Power BI, Excel, and basic scripting (SQL/Python a plus).
Collaboration tools (Teams, ServiceNow).
Preferred Qualifications
Familiarity with AI models and using AI to aid data analysis and anomaly detection.
Part 107 license to fly a drone is an advantage.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Analyst
Industries
Chemical Manufacturing and Oil and Gas
Inferred from the description for this job
Medical insurance
Vision insurance
401(k)
#J-18808-Ljbffr