Senior Engineer - Data Science

OCI Data Science Platform

Build, train, evaluate and deploy machine learning models using OCI Data Science, notebooks and Python-based ML solutions.

Data Preparation & Feature Engineering

Perform data cleansing, feature engineering, dataset management and model validation activities.

Machine Learning & Analytics

Develop supervised and unsupervised models including forecasting, classification, clustering and recommendation solutions.

Model Lifecycle & Governance

Manage model lifecycle, versioning, approvals, governance and traceability through OCI Model Catalog or equivalent controls.

MLOps & Deployment

Deploy models as scalable REST API endpoints and support CI/CD pipelines for model promotion and production deployment.

Monitoring & Continuous Improvement

Monitor model performance, utilisation and drift and support retraining and optimisation activities.

Operational Support

Provide L2/L3 support for deployed AI/ML solutions, troubleshooting, enhancements and knowledge base updates.

Primary Skills

• OCI Data Science
• Python
• SQL
• Machine Learning
• Model Validation
• Statistical Analysis

Secondary/ Support Skills

• OCI DevOps
• Docker
• Kubernetes
• Data Engineering concepts
• AI Governance
• Model monitoring

Tools/ Platforms

• Jupyter Notebooks
• TensorFlow
• PyTorch
• Scikit-learn
• OCI Object Storage
• Oracle Autonomous Database
• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering or a related field.
• Minimum 5 years of experience in data science, machine learning, advanced analytics or predictive modelling.
• Minimum 3 years of experience using OCI Data Science or equivalent cloud ML platforms.
• Experience developing, training, deploying and monitoring machine learning models in production environments.
• Strong understanding of MLOps, feature engineering, model governance and large-scale data analysis.
• OCI Data Science Professional, OCI AI Foundations Associate or OCI AI Professional certifications are preferred.