
Data Scientist
4 weeks ago
Competencies:
Collaborate with domain experts in the organization to understand design workflows extract actionable insights/opportunities.
Develop tools, scripts, or models to automate design and drafting workflows like drawing generation,clash detection, material estimation.
Analyze large volumes of design data like piping layouts, cable schedules, structural loads to derive insights or identify inconsistencies.
Design and implement ML models to optimize engineering workflows like drawing classification, component recognition, clash detection, layout optimization.
Develop AI-powered tools for drawing review, quantity take-off, change detection, and model validation.
Integrate AI models into engineering software environments and apply natural language processing (NLP) / computer vision techniques to automate tasks like image tagging, design pattern recognition, or content generation.
Build predictive or optimization models to support Structural load optimization, Cable routing and I/O allocation, Piping/material layout optimization.
Integrate with or extract data from 3D modeling tools (e.g., AVEVA E3D, AutoCAD, SmartPlant,MicroStation, STAAD, Tekla).
Stay up-to-date with the latest advancements in data science, machine learning, and design tools to continuously innovate and improve automation solutions.
Skills:
Overall 6+ years of experience in data science, machine learning frameworks and libraries .
Atleast 2 years of experience in O&G domain.
Proficiency in Python along with pandas, scikit-learn, PyTorch/TensorFlow libraries.
Experience with computer vision for drawing/model analysis.
Knowledge of data processing tools, techniques and working with large datasets.
Understanding of engineering documentation and deliverables: GA drawings, P&IDs, cable schedules, structural drawings.
- Strong problem-solving abilities, analytical thinking with an ability to troubleshoot and resolve issues.
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