Job Description Summary
The Data Scientist 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 machine learning and deep learning solutions focused on image and video analytics, including computer vision, image processing, multimodal models, statistical methods, and semantic analysis to extract structure and actionable insights from large-scale visual datasets. 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.
Job Description
Site Overview
Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.
Role Overview:
Understand business problems and implement Data Science solutions.
Design, develop, and implement computer vision, image processing, and multimodal deep learning solutions across engineering, services, and manufacturing use cases, including vision tasks such as classification, detection, segmentation, tracking, OCR, and self-supervised representation learning.
Explore, evaluate, and apply state-of-the-art architectures (e.g., CNNs, Vision Transformers, hybrid CNN‑ViT, diffusion-style, multimodal vision–language) tailored to aerospace imaging modalities.
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.
The Ideal Candidate
The ideal candidate should have 4+Years experience into development and deployment of machine learning and deep learning solutions focused on image and video analytics, including computer vision, image processing, multimodal models, statistical methods, and semantic analysis to extract structure and actionable insights from large-scale visual datasets.
Required Qualifications
Masters or PhD degree in Statistics, Machine Learning, Computer Science or related STEM fields (Science, Technology, Engineering and Math) with analytics development experience
Proficiency in Python (mandatory).
Proficiency in PyTorch/TensorFlow, CNNs, Vision Transformers, hybrid CNN–ViT, diffusion-style, multimodal vision–language & OCRs.
Familiarity with Python web frameworks.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
Influences within working team.
Implements component (s) of the roadmap.
Can use basic scripting tools to handle/read/retrieve/view different unstructured data types such as Images, Videos, Speech and Text from Database
Determines algorithms and pipelines needed to detect data errors and applies procedures for data quality assessment.
Performs missing data imputation/outlier removal/multicollinearity by using established GE techniques and domain knowledge.
Develops and improves models, performs trade-off analysis. Applies at least one modeling approach for the prevalent data types.
Can run and interpret black-box algorithms to builds models (random forests, neural networks, etc.,)
Ask relevant questions to stakeholders before setting up dashboards or reports.
Understands the Project applicability within GE Aerospace business.
At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.
Additional Information
Relocation Assistance Provided: No
