Power Gen Data Scientist — Predictive Maintenance

ProPetro Energy Solutions; Houston (TX); On-site; USD 110,000 - 140,000; Full time

Job summary

PROPWR's Data Scientist will support power generation operations by developing analytics, predictive models, and data-driven insights that improve asset performance, reliability, and operational efficiency. You will work with engineering, operations, and maintenance teams to analyze large datasets from assets, SCADA, and condition-monitoring platforms.

Key tasks include building forecasting models for generation output, identifying trends and anomalies, validating data quality, and turning

Qualifications

• Bachelor's degree in Data Science, Engineering, Mathematics, Statistics, Computer Science, or related field.
• 3–7 years of experience in data science, analytics, or applied machine learning.
• Strong experience with Python or R; SQL; Time series data analysis; Experience with operational or industrial datasets.

Responsibilities

• Analyze large datasets from power generation assets, SCADA systems, sensors, and historian platforms.
• Identify trends, anomalies, and performance deviations impacting asset reliability and availability.
• Validate and improve data quality across operational systems and data pipelines.
• Develop predictive models for equipment health, failure probability, and maintenance planning.

Skills

Python

R

SQL

Time series

Operational data

Education

Bachelor's degree

Job description

PROPWR's Data Scientist will support power generation operations by developing analytics, predictive models, and data-driven insights that improve asset performance, reliability, and operational efficiency. You will work with engineering, operations, and maintenance teams to analyze large datasets from assets, SCADA, and condition-monitoring platforms.

Key tasks include building forecasting models for generation output, identifying trends and anomalies, validating data quality, and turning