We are seeking an experienced Asset Predictive Analytics Engineer to join our team. The candidate will be responsible for developing, implementing, and maintaining predictive analytics models and solutions to optimize asset performance, reduce downtime, and improve overall efficiency. The ideal candidate will have a strong background in data analysis, machine learning, and programming, as well as experience working with the asset Oil & GAS industries.
Roles & Responsibilities:
- Develop and implement predictive analytics models and solutions to optimize asset performance, reduce downtime, and improve overall efficiency
- Collaborate with cross-functional teams to identify business problems and develop solutions using data-driven approaches
- 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, and develop insights to inform business decisions
- Develop and maintain databases and data systems to support predictive analytics applications
- Collaborate with stakeholders to develop and implement predictive analytics solutions that meet business needs
- Stay up-to-date with industry trends and emerging technologies in predictive analytics and machine learning
- Develop and maintain documentation of predictive analytics models, solutions, and results
Qualifications & Requirements:
- Reliability Engineering is preferable or Mechanical Engineer
- 5+ years of experience in predictive analytics, machine learning, or related field
- Experience working with asset-intensive industries (e.g. oil and gas, manufacturing, etc.)
- good programming skills in languages such as 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 deadlines
Preferences
Proficient in GE Smart signals, Backer-Hughes C3.AI , Aveva APA , AspenTech MTell
