
Sr. Data Scientist
- Houston, TX
- Permanent
- Full-time
- Define and guide the development of physics-ML reliability models (Weibull analysis, survival modeling, FMEA)
- Perform fluid-mechanics and mechanical simulations in Python or MATLAB and integrate outputs with telemetry streams
- Architect, deploy and monitor model training and serving pipelines on GCP AI Platform or Dataiku
- Establish validation protocols by coordinating with subject-matter experts to calibrate model assumptions
- Partner with maintenance, operations and field teams to align modeling efforts with business needs and data availability
- Identify new digital-twin use cases and build proof-of-concepts for early-warning systems and maintenance optimization
- Present technical findings to operations leadership, maintenance planners and engineering management
- Prior experience in equipment reliability, predictive maintenance or physics-based modeling in oil and gas
- Expert programming skills in Python (SciPy, NumPy) for simulation and model development
- Strong foundation in reliability engineering methods such as Weibull analysis, survival modeling and FMEA
- Strong communication skills with the ability to explain complex models to non-technical stakeholders
- Ability to manage multiple priorities and deliver results on time
- Bachelor's degree in Mechanical Engineering, Petroleum Engineering, Physics or related field
- 5+ years of experience applying physics-based modeling or reliability engineering in industrial settings
- 3+ years building and deploying data-science algorithms on cloud platforms (AWS, GCP or Azure)
- 3+ years developing simulation code in Python
- Master's degree or higher in a quantitative engineering or physical science discipline
- Research publications or patents in equipment reliability, preventative maintenance or related areas
- Prior field experience in equipment maintenance
- Experience integrating physics-based models with machine-learning frameworks such as TensorFlow or PyTorch