Description

You will develop and deliver analytics models for equipment condition monitoring, focusing on failure prediction and remaining life estimation.

This role is on-site.

Responsibilities

• Collect and negotiate requirements for condition monitoring models.
• Access, cleanse, and preprocess time-series machine sensor data and service records.
• Develop, backtest, and validate machine learning and statistical models in Python.
• Compute model performance metrics and explain decisions to stakeholders.
• Support models in production and resolve incident tickets.

Required Skills

• Python proficiency with NumPy, Pandas, Matplotlib, and Scikit-learn.
• SQL and database APIs (cx_Oracle, PyMySQL, SQLAlchemy).
• Cloud deployment on AWS (S3, EC2, SageMaker) and containerization.
• Version control using Git.
• Experience working within Agile/Scrum environments.
• Bachelor's degree in Data Science, CS, Engineering, or related field with 2-4 years experience (or Master's/PhD with 1-2 years).
• Strong critical thinking and independent problem-solving abilities.

Preferred Skills

• Machine learning model development and multiprocessing frameworks.
• Familiarity with engineering/IoT systems and telematics/time-series data analysis.

Key Skills

Education

Any Graduate