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Data Science Specialist

GE Aerospace -
Bengaluru, Karnataka

Apply Now

Job details

Full-time

Qualifications

CI/CD
Statistics
Azure
Statistics
Law
Doctoral degree
Computer Science
Git
Google Cloud Platform
Master's degree
SQL
AWS
Math
Docker
Machine learning
Continuous integration
GitHub
Data science
Data visualization
AI
Graph databases
Python
Analytics

Full job description

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, semantic analysis etc. 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.

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 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.

The Ideal Candidate

The ideal candidate should have experience in Gen AI/LLM, python and SQL.

Required Qualifications:

Master’s 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 and SQL (mandatory).
Familiarity with Python web frameworks.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services
Awareness of Knowledge Graphs
Utilize Docker for containerization of application services.
Implement and maintain CI/CD pipelines (e.g., GitHub Actions, AWS CodeBuild/CodePipeline) and use Git for version control.
Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on datasets
Demonstrated skill at data visualization and storytelling for an audience of stakeholders

Preferred Qualifications:

Influences within peer group.
Implements specific component(s) of the roadmap.
Evaluates features using well known or prescribed recipes and appropriately down selects to valuable ones.
Aware of models such as CART / SVM / RF / Neural Net and the associated sub-models
Knowledge on Gen AI/LLM
Uses Cross Validation and other Verification & Validation techniques to build robust models from large data sets.
Understands the types of issues that impact data quality
Performs basic data cleaning operations such as flagging missing and invalid data etc.
Fits normal parameters to data and assess goodness of fit
Can use and interpret t-tests, ANOVA and basic hypothesis testing with good utilization of p-values.
Codes using modular practices for reusage and object-oriented Effectively shows visualization of data exploration using box, bubble and matrix plots.
Has a basic understanding of GE Aerospace business and how the tools they are developing create value.

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

Apply Now

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