Staff Data Scientist
| Company | GE Aerospace |
|---|---|
| Location | Atlanta, GA, USA, Decatur, GA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree from accredited university or college with minimum of 3 years of professional experience OR an associate’s degree with minimum of 5 years of professional experience
- 3 years of proficiency in Python (mandatory)
- 2 years’ experience with machine learning frameworks and deploying models into production environments
Responsibilities
- Design, develop, and deploy machine learning models and algorithms
- Understand business problems and identify opportunities to implement data science solutions.
- Develop, verify, and validate analytics to address customer needs and opportunities.
- Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
- Develop and maintain pipelines for Retrieval-Augmented Generation (RAG) and Large Language Models (LLM).
- Ensure efficient data retrieval and augmentation processes to support LLM training and inference.
- Utilize semantic and ontology technologies to enhance data integration and retrieval. Ensure data is semantically enriched to support advanced analytics and machine learning models.
- Participate in Data Science Workouts to shape Data Science opportunities and identify opportunities to use data science to create customer value.
- Perform exploratory and targeted data analyses using descriptive statistics and other methods.
- Work with data engineers on data quality assessment, data cleansing, data analytics, and model productionization
- Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
- Communicate methods, findings, and hypotheses with stakeholders.
Preferred Qualifications
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.
- Experience with handling unstructured data, including images, videos, and text.
- Understanding of computer vision techniques and tools
- Ability to work in a fast-paced, dynamic environment.
- Experience with data preprocessing and augmentation tools.
- Demonstrated expertise in critical thinking and problem-solving methods
- Familiarity with cloud platforms (e.g. AWS, Azure, Google Cloud, Databricks) and their machine learning services
- Demonstrated skill in defining and delivering customer value.
- Demonstrated expertise working in team settings in various roles
- Demonstrated expertise in presentation and communications skills.
- Experience with deep learning and neural networks.
- Knowledge of data governance and compliance standards.