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Job Title: Asset Predictive Analytics Engineer

Employment Type: Full-time

About the Role
Are you passionate about using data to drive reliability and operational excellence? We are seeking an experienced Asset Predictive Analytics Engineer to join our team and lead the development of cutting-edge predictive models that optimize asset performance, reduce downtime, and maximize efficiency. If you have a strong background in machine learning and hands-on experience in asset-intensive industries like Oil & Gas, we want to hear from you.

What You’ll Do

Develop and implement predictive analytics models and solutions to optimize asset performance, reduce downtime, and improve overall efficiency.

Collaborate with cross-functional teams (engineering, maintenance, operations) to identify business problems and develop data-driven solutions.

Design, develop, and deploy machine learning models and algorithms to predict asset failures, detect anomalies, and optimize maintenance schedules.

Work with large datasets to identify trends, patterns, and correlations, translating insights into actionable business decisions.

Develop and maintain databases and data systems to support predictive analytics applications.

Partner with stakeholders to implement solutions that meet real-world operational needs.

Stay current with industry trends and emerging technologies in predictive analytics and machine learning.

Create and maintain thorough documentation of predictive models, solutions, and results.

What You Bring (Qualifications & Requirements)

Education: Bachelor’s degree in Reliability Engineering, Mechanical Engineering, or a related field (Advanced degree preferred).

Experience: 5+ years in predictive analytics, machine learning, or a related field.

Industry background: Experience working in asset-intensive industries – Oil & Gas, manufacturing, petrochemical, or power generation.

Programming skills: Proficiency in Python, R, or SQL.

Strong data analysis and problem-solving skills.

Excellent communication and collaboration skills.

Ability to work in a fast-paced environment and meet tight deadlines.

Preferred Qualifications (Highly Valued)
Proficiency with one or more of the following platforms:

GE SmartSignal

Baker Hughes C3.AI

Aveva Predictive Analytics (APA)

AspenTech Mtell

Why Join Us?

Work on high-impact assets in the Oil & Gas sector.

Access to industrial datasets and real-world reliability challenges.

Opportunity to deploy models that directly reduce downtime and save costs.

Collaborate with reliability engineers, data scientists, and operations leaders.

[Add your benefits: competitive salary, performance bonus, health insurance, training budgets, etc.]