Data Science(RARR Job 5039)

We are seeking a highly skilled and experienced Senior Data Scientist  Machine Learning Engineer to join our team in the oil and energy sector This role requires a unique blend of data science expertise and machine learning engineering capabilities The ideal candidate will have 810 years of experience developing and deploying robust scalable machine learning solutions in complex industrial environments

Responsibilities

Data Science  Machine Learning

• Develop and implement advanced machine learning models for predictive maintenance production optimization reservoir modeling and risk assessment specific to the oil and energy industry
• Conduct indepth data analysis and feature engineering to identify patterns and insights from large datasets
• Machine Learning Engineering
• Design build and deploy scalable machine learning pipelines and infrastructure
• Develop and maintain machine learning models in production environments ensuring performance reliability and security
• Implement machine learning operations MLOps practices for continuous integration and continuous delivery CICD of models
• Optimize machine learning models for performance and efficiency considering resource constraints and realtime requirements
• Work with cloud platforms eg AWS Azure GCP to deploy and manage machine learning infrastructure
• Containerize and deploy models using Docker and Kubernetes
• Oil and Energy Domain Expertise
• Apply deep understanding of oil and gas operations including upstream midstream and downstream processes
• Collaborate with domain experts to identify opportunities for machine learning applications
• Translate business requirements into technical specifications for machine learning solutions
• Collaboration and Communication
• Work closely with data engineers software developers and domain experts to deliver highquality machine learning solutions
• Communicate complex technical concepts to nontechnical audiences
• Mentor junior data scientists and machine learning engineers
• Model Maintenance and Monitoring
• Monitor model performance in production and implement strategies for model retraining and updating
• Troubleshoot and resolve issues related to machine learning models and infrastructure

Qualifications

• Masters or PhD in Computer Science Machine Learning Statistics or a related field
• 8 to 10 years of experience in data science and machine learning engineering
• Strong programming skills in Python and relevant machine learning libraries eg scikitlearn TensorFlow PyTorch
• Experience with cloud platforms AWS Azure GCP and containerization technologies Docker Kubernetes
• Proven experience in deploying machine learning models in production environments
• Strong understanding of machine learning algorithms and statistical modeling
• Deep understanding of the Oil and Energy domain
• Excellent problem solving and communication skills

Preferred Skills

• Experience with MLOps tools and practices
• Knowledge of database systems and data warehousing
• Experience with real time data processing