Data Scientist

• 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 should have experience in Gen AI/LLM, python.
  

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

Additional Information

Relocation Assistance Provided: