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ELUTIONS is a global provider of Operational Business Intelligence and AI-driven solutions that optimize a broad range of operational performance and business practices-including, but not limited to, resource efficiency and energy consumption, production, asset health and performance, and commercial and logistics operations-across asset-intensive industries, such as chemical, LNG, refining, manufacturing, and logistics sectors. With over 30 years of experience evolving from industrial automation and controls into advanced AI analytics, Elutions enables organizations to convert operational data into actionable insights that drive measurable business outcomes.

At Elutions, engineers work closely with real operational systems and data, gaining hands-on experience in applying analytics to complex, asset-intensive environments. Team members are encouraged to continuously develop their technical and domain expertise while contributing to solutions that deliver measurable operational and business impact.

The Engineering Team is seeking a motivated Domain Engineer with the ability to integrate optimization strategies into real-world applications through commissioning data analytics and implementation.

This position is primarily in-person with intermittent travel. Both entry- and mid-level applicants are encouraged to apply, as on-the-job training and mentorship are provided to support professional growth and technical development.

** Entry Level Candidates are Encouraged to Apply!!!**

General Responsibilities:

• Conduct research, data analytics, and prepare technical and performance reports.
• Develop an understanding of industrial process systems and operations, including (but not limited to) fluid mechanics, pumping systems, energy systems, wastewater treatment, desalination, and process operations across chemical, petroleum, LNG, and refinery sites.
• Analyze large operational datasets and apply data analytics and data-mining concepts to identify patterns, anomalies, and optimization opportunities.
• Read and understand asset performance curves and equipment specifications.
• Learn and implement technical hardware/software solutions for monitoring, analytics, and optimization.
• Apply data pattern recognition techniques and energy optimization methodologies to support operational improvement initiatives.
• Visualize data findings through dashboards including UI/UX design
• Provide second-tier customer support for deployed analytics and optimization solutions.
• Support customer engagement activities, including training sessions, software demonstrations, technical presentations, and any additional support.
• Have effective interpersonal skills, organization/prioritization and administrative skills
• Field travel as needed to perform site surveys, equipment installation/commissioning, and field support activities.

Requirements:

• Master's degree or Bachelor's degree in either Mechanical Engineering, Chemical Engineering, Petroleum Engineering, Electrical Engineering, or Industrial Engineering disciplines. Other high-level science or mathematics-based degrees will also be considered.
• Proficiency in Microsoft Excel for data analysis (formulas, pivot tables, charts).
• Working knowledge of Python or a similar scripting language for data analysis.
• Basic understanding of data analytics and statistics, including trend analysis and anomaly detection.
• Ability to interpret process diagrams and technical documentation (PFDs, P&IDs, equipment data).
• Exposure to industrial or operational data systems (e.g., historians, DCS/SCADA) is preferred.

Motivational Fit:

The successful candidate will have the following attributes:

• Strong written and verbal communication skills, particularly when collaborating with distributed or cross-functional teams.
• Ability to plan, organize, and prioritize work effectively across multiple tasks and timelines.
• Analytical and creative problem-solving skills, with a willingness to investigate complex technical challenges.
• Proactive mindset with the ability to take initiative and follow through on assignments.
• Flexibility and adaptability when working in dynamic technical and operational environments.
• Collaborative, team-oriented approach with a strong sense of accountability.
• High level of motivation and interest in continuous learning and professional development.