Data Science Specialist

Summary
The Data Science Specialist will work in cross-functional teams addressing statistical analysis, machine learning, and data understanding problems in a commercial technology and consultancy development environment. In this role, you will contribute to the development, deployment, and operationalization of Generative AI (GenAI) solutions alongside developing machine learning, operational research, semantic analysis, and statistical methods for finding structure in large, complex data sets.

Company Overview
Working at GE Aerospace means you are bringing your unique perspective, innovative spirit, drive, and curiosity to a collaborative and diverse team working to advance aerospace for future generations. If you have ideas, we will listen. Join us and see your ideas take flight!
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
As a Data Science Specialist, you will be part of a data science or cross-disciplinary team on commercially-facing development projects, typically involving large, complex data sets. These teams typically include statisticians, computer scientists, software developers, engineers, product managers, and end users, working in concert with partners in GE business units. Potential application areas include remote monitoring and diagnostics across infrastructure and industrial sectors, financial portfolio risk assessment, and operations optimization.

• Develop analytics within well-defined projects to address customer needs and opportunities.
• Work alongside software developers and software engineers to translate algorithms into commercially viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.

• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Share and discuss findings with team members.
  

The Ideal Candidate

• Ideal candidate should have experience in GEN AI, NLP, LLM, Image Analytics, Python and cloud platforms
  

Required Qualifications

• Bachelors Degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math) with advanced experience.
• Proven experience in developing and deploying NLP models, particularly large language models (LLMs) and agentic AI systems.
• Strong programming skills in Python and familiarity with NLP libraries and frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, Langchain, Langgraph and spaCy.
• Experience with cloud platforms and tools for deploying machine learning models (e.g., AWS, GCP, Azure).
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Experience with transfer learning, fine-tuning, and prompt engineering for LLMs.
• Knowledge of agentic AI principles and their application in real-world scenarios.
• Familiarity with big data technologies and tools such as Hadoop, Spark, and SQL.
• Publications or contributions to the NLP and AI research community.
  

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: Yes