Power Gen Data Scientist: Predictive Analytics & Reliability

ProPetro Services, Inc; Houston (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

PROPWR, Houston-based energy analytics leader, seeks a Data Scientist to turn raw operational data from power generation assets, SCADA, and historians into actionable insights that reduce downtime and optimize maintenance. You will build predictive models, dashboards, and KPI reports for engineering and operations, collaborating across teams to drive reliability and efficiency.

The role requires 3–7 years in data science, strong Python/R and SQL skills, and experience with time-series data in

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.
• Statistical modeling and machine learning techniques.
• Time series data analysis.
• Experience working with operational or industrial datasets.
• Ability to communicate complex analytical concepts clearly and effectively.

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.
• Build forecasting models for generation output, performance, and reliability.
• Support reliability engineering by providing data-driven insights into failure mechanisms and asset risks.
• Conduct hypothesis testing and statistical analysis to validate assumptions and guide engineering decisions.
• Build dashboards, KPIs, and performance reporting tools for engineering and operations teams.
• Translate complex analytical findings into clear, actionable recommendations for non-technical stakeholders.
• Partner with Operations, Maintenance, and Engineering to turn insights into operational improvements.
• Support root cause analysis (RCA) investigations with data-driven evidence and modeling.
• Work with reliability engineers to integrate predictive analytics into maintenance strategies.
• Document models, assumptions, methodologies, and business impact.
• Maintain version control, code quality, and reproducibility standards.
• Support deployment of models into production environments when applicable.
• Stay current with emerging analytics tools, machine learning techniques, and power-generation technologies.
• Maintain compliance with Health, Safety, and Environment (HSE) policies by attending all required HSE training sessions, safety meetings, and always utilize proper Personal Protective Equipment (PPE)
• Other duties as assigned

Skills

Python

R

SQL

Time series analysis

Statistical modeling

Communication

Education

Bachelor’s degree in Data Science or related field

Job description

PROPWR, Houston-based energy analytics leader, seeks a Data Scientist to turn raw operational data from power generation assets, SCADA, and historians into actionable insights that reduce downtime and optimize maintenance. You will build predictive models, dashboards, and KPI reports for engineering and operations, collaborating across teams to drive reliability and efficiency.

The role requires 3–7 years in data science, strong Python/R and SQL skills, and experience with time-series data in