Sr Data Scientist

Job description

Job Description Summary

The Sr 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 modern machine learning, artificial intelligence, statistical methods, operations research, semantic analysis etc. for finding structure in large data sets. The candidate will be responsible for executing data science projects independently to deliver business outcomes and is expected to demonstrate domain expertise, develop, and execute program plans and proactively solicit feedback from stakeholders to identify improvement actions. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams.

Job Description

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:

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Understand business problems and identify opportunities to implement Data Science solutions.

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Design, develop, and implement machine learning and artificial intelligence models and algorithms.

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Understand various business processes pertaining to Analytics Development Process

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Collect, preprocess, and analyze large datasets to be used for training and testing machine learning models.

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Ensure data quality and integrity throughout the data pipeline.

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Conduct experiments to develop model and evaluate model performance and iterate on model improvements.

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Work with Data Engineering teams to deploy data science models into production environments.

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Monitor and maintain deployed models to ensure they perform as expected.

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Work closely with data architects, data engineers, and other stakeholders to understand business requirements and translate them into technical solutions.

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Provide technical support and guidance on machine learning-related issues.

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Optimize machine learning models for performance, scalability, and efficiency.

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Implement techniques to improve model accuracy and reduce computational costs.

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Stay up to date with the latest advancements in machine learning and artificial intelligence.

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Explore and implement new machine learning and artificial intelligence techniques and tools to enhance the team's capabilities.

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Maintain comprehensive documentation of machine learning models, algorithms, and processes.

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Ensure knowledge transfer and continuity within the team.

Ideal Candidate

Ideal candidate should have experience in AI& ML with strong python programming

Preferred Qualifications:

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Masters or PhD degree in Statistics, Machine Learning, Computer Science or related STEM fields (Science, Technology, Engineering and Math) with analytics development experience

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Proficiency in Python (mandatory).

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Strong analytical and problem-solving skills.

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Excellent communication and collaboration abilities.

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Ability to work in a fast-paced, dynamic environment.

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Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.

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Familiarity with Python web frameworks

Qualifications/ Requirements

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Influences PBs on their decisions.

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Implements a roadmap.

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Evaluates, down selects, and has awareness of advanced models for deriving new features in relation to the source of data.

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Can fit parameters for complex physics models.

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Develops ongoing hypothesis testing for model validity.

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Runs change point assessments and predictive models to project time series.

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Executes validation reproducibility, and deployment criteria.

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Able to use a variety of approaches (sequential sampling/ experimentation and observational studies) to generate cost-effective and representative samples.

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Understand advanced methods to trade off interpretability vs predictive complexity.

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Can articulate the top pitfalls and misleading graphical representations.

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Proficient with local and distributed operating environments.

Desirable Qualification

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Humble: respectful, receptive, agile, eager to learn

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Transparent: shares critical information, speaks with candor, contributes constructively

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Focused: quick learner, strategically prioritizes work, committed

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Leadership ability: strong communicator, decision-maker, collaborative

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Problem solver: analytical-minded, challenges existing processes, critical thinker

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