Data Insights Analyst

PTS Advance•Brentwood, TN

About The Position

Job Summary: The Data Insights Analyst transforms refinery operational data into actionable insights, and work 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 .

Requirements

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 interprete 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 staekholders.
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).

Nice To Haves

Familariy with AI models and using AI to aid data analysis and anomaly detection.
Part 107 license to fly a drone is an advantage.

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 escalate critical issues through established workflows.
In the near future work with AI models to aid in data anlysis and anomaly detection.
Risk Identification & Communication 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.
Collaboration & Reporting Partner with othe teams such as operations, reliability, maintenance, and process engineering teams to interpret insights and validate risks.
Document findings and recommendations.
Provide actionable intelligence.
Recommend improvements in data collection, monitoring strategy, and predictive maintenance programs.
Supporting the Drone Program (an option) Conduct remote visual inspections using the drones in the refineries.