The Role
Lead data science for asset reliability: develop predictive maintenance, digital twins, anomaly detection, and probabilistic reliability models; mentor teams and deliver operational, safety, and cost-saving outcomes in oil & gas.
Summary Generated by Built In
- The Principal Data Scientist will lead Data Science for Asset Reliability and Cognition portfolio to innovate and mature prognosis models for industrial equipment’s, models to optimize maintenance strategies, and reduce operational risk.
- This role requires a blend of machine learning expertise, reliability engineering knowledge, and oil & gas domain experience to drive measurable impact across critical assets.
- Also required is a customer-oriented focus by acknowledging their needs and offering pragmatic customer solutions that align with their data capabilities.
Key Responsibilities
- Predictive maintenance: Design and deploy ML models to forecast equipment failures and optimize maintenance schedules.
- Digital twin development: Build hybrid AI + physics-based models to simulate asset health and performance.
- Advanced anomaly detection: Implement deep learning and unsupervised methods for early detection of vibration, corrosion, and fouling.
- Reliability analytics: Apply Bayesian networks, causal inference, and probabilistic modeling to identify root causes of failures.
- Cross-functional leadership: Mentor data science teams, collaborate with engineers, and influence executive stakeholders.
- Research and maintain a deep knowledge of the industry, including trends and technologies to identify strategy opportunities and contribute to thought leadership best practices.
Qualifications
- PhD or Master’s in Data Science, Reliability Engineering, Chemical/Mechanical Engineering, or Applied Mathematics.
- 12+ years of industrial analytics experience, with at least 5 years in oil & gas reliability.
- Expertise in time-series forecasting, reinforcement learning, graph neural networks.
- Proficiency in Python, R, Scala, Spark, Hadoop, and cloud-native ML platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
- Familiarity with asset reliability standards.
- Experience in risk-based inspection (RBI), HAZOP analytics, and probabilistic reliability modeling.
Focus Area Contribution:
- Asset Reliability: Extend asset life cycles and reduce catastrophic failures.
- Operational Excellence: Integrate ML with process simulators for refinery-wide optimization.
- Cost Reduction: Deliver multimillion-dollar savings via predictive maintenance and inventory optimization.
- Safety & ESG: Enhance compliance and reduce environmental incidents through proactive monitoring.
- Digital Transformation: Champion AI adoption across enterprise reliability programs.
Skills Required
- PhD or Master's in Data Science, Reliability Engineering, Chemical/Mechanical Engineering, or Applied Mathematics
- 12+ years of industrial analytics experience
- At least 5 years experience in oil & gas reliability
- Expertise in time-series forecasting, reinforcement learning, and graph neural networks
- Proficiency in Python, R, Scala, Spark, and Hadoop
- Experience with cloud-native ML platforms (Azure ML, AWS SageMaker, GCP Vertex AI)
- Familiarity with asset reliability standards
- Experience in risk-based inspection (RBI), HAZOP analytics, and probabilistic reliability modeling
Honeywell Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.
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Retirement Support — Retirement plans feature a notably strong company 401(k) match with vesting after three years, enhancing long-term savings security. Additional tax-advantaged accounts and company contributions for eligible earners further strengthen financial preparedness.
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Leave & Time Off Breadth — Time off policies include flexible or unlimited vacation for many salaried roles and a broad observed-holiday schedule, providing manager-approved flexibility. This structure supports rest and work-life balance across varied needs.
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Parental & Family Support — Parental leave offers paid time for birth, adoption, or foster care that can be taken consecutively or intermittently. The design enables practical flexibility in how family leave is used.
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The Company
What We Do
Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.
