Data Collection and Preprocessing
Collect and process structured and unstructured datasets from engineering systems, databases, and operational tools.
Clean and validate datasets to ensure accuracy and consistency.
Develop scripts and pipelines for data preprocessing and transformation.
Exploratory Data Analysis
Perform exploratory analysis to identify patterns, correlations, and insights within datasets.
Investigate data quality issues and anomalies that may impact model development.
Machine Learning Model Development
Implement machine learning algorithms such as regression, classification, clustering, and anomaly detection.
Support feature engineering and model training workflows.
Evaluate model performance using statistical and machine learning metrics.
Model Deployment and Integration
Assist in deploying machine learning models into production systems.
Support integration of models into engineering tools, APIs, and data pipelines.
Work with software engineers to ensure models operate reliably in production environments.
Performance Monitoring
Monitor deployed models for accuracy and performance degradation.
Support retraining and model updates when data drift occurs.
