DISA Technologies, Inc.
About Us
DISA Technologies is revolutionizing mineral recovery with our patented High-Pressure Slurry Ablation (HPSA) technology—an innovative solution that upgrades critical minerals from mined ore and legacy waste. Serving both the mining and remediation sectors, we recover valuable resources that power industry, strengthen energy independence, and restore contaminated sites to productive use. Our technology unlocks economic and environmental value, transforming how the world processes, remediates, and recycles essential mineral assets.
Job Summary The Analytics Engineer designs, builds, and deploys advanced analytics and machine learning solutions to support DISA's mineral recovery and remediation operations. This role applies AI/ML, numerical modeling, and statistical analysis to complex industrial data (e.g. time-series sensor data, particle size distributions, real-time process data) to improve equipment reliability, maintenance strategies, and process performance. The position works closely with engineering, operations, and maintenance teams to deliver practical, data-driven solutions that improve design decisions and operational efficiency in real-world environments. The ideal candidate will have experience in applied mathematics and data analysis, with the ability to translate advanced concepts into working solutions in a fast-paced environment.
Education and Experience
Bachelor's degree in Chemical Engineering, Mechanical Engineering, Industrial Engineering, Reliability Engineering, Data Analytics, Applied Mathematics, or a related technical discipline required
3-7 years of experience in one or more of the following preferred:
Preventive or predictive maintenance modeling
Reliability or asset management engineering
Industrial analytics or operations data analysis
Applied machine learning in industrial or physical systems
Demonstrated experience analyzing large operational data sets (sensor data, maintenance logs, inspections, downtime, and performance metrics)
Experience in industrial environments such as mining, manufacturing, chemicals, energy, or minerals processing is strongly preferred
Candidates with backgrounds in reliability engineering, preventive maintenance, industrial operations, or field engineering who have applied AI or advanced analytics are strongly preferred
Supervisor Senior Process Engineer, unless otherwise designated.
Typical Job Duties And Responsibilities
Analyze equipment, sensor, and maintenance data to identify degradation trends, failure modes, and reliability risks
Develop and deploy AI- and ML-enabled models for predictive maintenance, condition monitoring, and remaining useful life (RUL) estimation
Translate field and maintenance data into actionable insights that support design improvements and operational decisions
Partner with operations and maintenance teams to ensure analytical models align with real-world workflows and constraints
Apply advanced analytics to improve inspection strategies, spare parts planning, maintenance intervals, and asset performance
Support continuous improvement initiatives by quantifying the impact of design, process, or operational changes
Develop, review, and refine machine learning models supporting HPSA process optimization and predictive analytics
Apply numerical methods, statistical learning, and data-driven modeling to enhance system monitoring and control
Support integration of analytics and ML pipelines into production and operational systems
Document methodologies, maintain codebases, and ensure reproducibility and usability of results
Collaborate with all internal disciplines, and manage external partners, as necessary, on projects
Implement shape- and geometry-based statistical tools for manufacturing process monitoring
Support the integration of machine learning pipelines into production systems
Document methods, maintain codebases, and ensure reproducibility of results
Abide by all policies and procedures established by DISA
Attend and participate in all required safety trainings.
Assist with any task required by the direct supervisor.
Requirements
Strong understanding of industrial systems, equipment behavior, and preventive maintenance concepts
Ability to analyze large, complex operational data sets and identify performance or reliability drivers
Experience with control systems or SCADA data and SQL databases
Practical experience applying AI or machine learning to physical systems (predictive maintenance, anomaly detection, optimization)
Proficiency in Python and common data analysis / ML libraries (scikit-learn, PyTorch, TensorFlow, or similar)
Experience working with time-series data, sensor data, or maintenance records
Working knowledge of statistics, reliability analysis, and data-driven modeling
Ability to communicate analytical insights clearly to non-data specialists
Apply strong analytical and problem-solving skills to manage multiple projects effectively
Communicate clearly and professionally, both verbally and in writing, to collaborate with colleagues, stakeholders, and clients
Organize and prioritize tasks to meet deadlines while managing multiple projects
Collaborate effectively as part of a team, supporting shared goals and fostering positive relationships
Adapt to dynamic environments and identify solutions to challenges with flexibility and problem-solving skills
Maintain professionalism with high attention to detail, reliability, accountability, and accuracy in all work deliverables
Uphold and demonstrate DISA's Values of Dedication, Innovation, Sustainability, and Accelerate Change
Ability to follow safety protocols and maintain compliance with OSHA/MSHA and company safety standards
Be a valid U.S. citizen or legally authorized to work in the United States
Possess a valid driver's license with a clean driving record
Physical Requirements
Must be able to relocate to Casper, WY
Must be able to sit and/or stand for extended periods of time
Must be able to lift up to 25 lbs. occasionally
Must be able to interact with people and technology while either standing or sitting
To best service our customers, all employees must be able to communicate face-to-face and on the phone with or without reasonable accommodation
Ability to travel up to 50%.
Must be able to perform repetitive tasks such as typing
EEO Statement DISA Technologies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.
Benefits
Bonus Pool
401(k) with matching up to 4%
Employee stock options
Health insurance
Dental insurance
Vision insurance
Life insurance
Paid holidays
Paid time off
Professional Development
Seniority level Mid-Senior level
Employment type Full-time
Industries IT Services and IT Consulting
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Job Summary The Analytics Engineer designs, builds, and deploys advanced analytics and machine learning solutions to support DISA's mineral recovery and remediation operations. This role applies AI/ML, numerical modeling, and statistical analysis to complex industrial data (e.g. time-series sensor data, particle size distributions, real-time process data) to improve equipment reliability, maintenance strategies, and process performance. The position works closely with engineering, operations, and maintenance teams to deliver practical, data-driven solutions that improve design decisions and operational efficiency in real-world environments. The ideal candidate will have experience in applied mathematics and data analysis, with the ability to translate advanced concepts into working solutions in a fast-paced environment.
Education and Experience
Bachelor's degree in Chemical Engineering, Mechanical Engineering, Industrial Engineering, Reliability Engineering, Data Analytics, Applied Mathematics, or a related technical discipline required
3-7 years of experience in one or more of the following preferred:
Preventive or predictive maintenance modeling
Reliability or asset management engineering
Industrial analytics or operations data analysis
Applied machine learning in industrial or physical systems
Demonstrated experience analyzing large operational data sets (sensor data, maintenance logs, inspections, downtime, and performance metrics)
Experience in industrial environments such as mining, manufacturing, chemicals, energy, or minerals processing is strongly preferred
Candidates with backgrounds in reliability engineering, preventive maintenance, industrial operations, or field engineering who have applied AI or advanced analytics are strongly preferred
Supervisor Senior Process Engineer, unless otherwise designated.
Typical Job Duties And Responsibilities
Analyze equipment, sensor, and maintenance data to identify degradation trends, failure modes, and reliability risks
Develop and deploy AI- and ML-enabled models for predictive maintenance, condition monitoring, and remaining useful life (RUL) estimation
Translate field and maintenance data into actionable insights that support design improvements and operational decisions
Partner with operations and maintenance teams to ensure analytical models align with real-world workflows and constraints
Apply advanced analytics to improve inspection strategies, spare parts planning, maintenance intervals, and asset performance
Support continuous improvement initiatives by quantifying the impact of design, process, or operational changes
Develop, review, and refine machine learning models supporting HPSA process optimization and predictive analytics
Apply numerical methods, statistical learning, and data-driven modeling to enhance system monitoring and control
Support integration of analytics and ML pipelines into production and operational systems
Document methodologies, maintain codebases, and ensure reproducibility and usability of results
Collaborate with all internal disciplines, and manage external partners, as necessary, on projects
Implement shape- and geometry-based statistical tools for manufacturing process monitoring
Support the integration of machine learning pipelines into production systems
Document methods, maintain codebases, and ensure reproducibility of results
Abide by all policies and procedures established by DISA
Attend and participate in all required safety trainings.
Assist with any task required by the direct supervisor.
Requirements
Strong understanding of industrial systems, equipment behavior, and preventive maintenance concepts
Ability to analyze large, complex operational data sets and identify performance or reliability drivers
Experience with control systems or SCADA data and SQL databases
Practical experience applying AI or machine learning to physical systems (predictive maintenance, anomaly detection, optimization)
Proficiency in Python and common data analysis / ML libraries (scikit-learn, PyTorch, TensorFlow, or similar)
Experience working with time-series data, sensor data, or maintenance records
Working knowledge of statistics, reliability analysis, and data-driven modeling
Ability to communicate analytical insights clearly to non-data specialists
Apply strong analytical and problem-solving skills to manage multiple projects effectively
Communicate clearly and professionally, both verbally and in writing, to collaborate with colleagues, stakeholders, and clients
Organize and prioritize tasks to meet deadlines while managing multiple projects
Collaborate effectively as part of a team, supporting shared goals and fostering positive relationships
Adapt to dynamic environments and identify solutions to challenges with flexibility and problem-solving skills
Maintain professionalism with high attention to detail, reliability, accountability, and accuracy in all work deliverables
Uphold and demonstrate DISA's Values of Dedication, Innovation, Sustainability, and Accelerate Change
Ability to follow safety protocols and maintain compliance with OSHA/MSHA and company safety standards
Be a valid U.S. citizen or legally authorized to work in the United States
Possess a valid driver's license with a clean driving record
Physical Requirements
Must be able to relocate to Casper, WY
Must be able to sit and/or stand for extended periods of time
Must be able to lift up to 25 lbs. occasionally
Must be able to interact with people and technology while either standing or sitting
To best service our customers, all employees must be able to communicate face-to-face and on the phone with or without reasonable accommodation
Ability to travel up to 50%.
Must be able to perform repetitive tasks such as typing
EEO Statement DISA Technologies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.
Benefits
Bonus Pool
401(k) with matching up to 4%
Employee stock options
Health insurance
Dental insurance
Vision insurance
Life insurance
Paid holidays
Paid time off
Professional Development
Seniority level Mid-Senior level
Employment type Full-time
Industries IT Services and IT Consulting
#J-18808-Ljbffr