Data Science Specialist Jobs at GE Aerospace - Apply Now | Bengaluru

Job Description Summary

The Data Science Specialist will develop and implement Artificial Intelligence based solutions across various disciplines in GE Aerospace. In this role, the candidate will contribute to the development and deployment of modern machine learning, artificial intelligence, statistical methods, operations research, and semantic analysis for finding structure in large data sets. The candidate will be responsible for executing data science projects under limited guidance from senior members to deliver business outcomes. This role requires a good technical background, strong problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams.

Role Overview

• Understand business problems and implement Data Science solutions.
• Design, develop, and implement machine learning and artificial intelligence models and algorithms.
• Understand various business processes pertaining to Analytics Development Process.
• Collect, preprocess, and analyze large datasets to be used for training and testing machine learning models.
• Ensure data quality and integrity throughout the data pipeline.
• Conduct experiments to develop model and evaluate model performance and iterate on model improvements.
• Under the guidance of senior members, work with Data Engineering teams to deploy data science models into production environments.
• Monitor and maintain deployed models to ensure they perform as expected.
• Under the guidance of senior members, work closely with data architects, data engineers, and other stakeholders to understand business requirements and translate them into technical solutions.
• Optimize machine learning models for performance, scalability, and efficiency.
• Be aware of latest advancements in machine learning and artificial intelligence.
• Explore and implement new machine learning and artificial intelligence techniques and tools to enhance the team's capabilities.
• Maintain comprehensive documentation of machine learning models, algorithms, and processes.