Collaborate with cross-functional teams to identify and define data requirements, data collection methods, and data quality standards
Build systems that enable conducting data analysis and exploration to identify patterns, trends, and insights that drive decision-making
Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments
Collaborate with subject matter experts to understand engineering domain knowledge and incorporate it into data analysis and modeling efforts
Continuously evaluate and improve existing models and algorithms to enhance their accuracy, efficiency, and scalability
Ensure data security, privacy, and compliance with relevant regulations and policies throughout the data analysis lifecycle
Stay up-to-date with the latest advancements in data science, machine learning, and aerospace technologies to drive innovation and maintain a competitive edge
Communicate findings, insights, and recommendations to technical and non-technical stakeholders through clear and concise reports, presentations, and visualizations
Mentor and provide guidance to junior data scientists

Bachelor’s degree from an accredited course of study in Mathematics, Data Science, Computer Science, Engineering, Physics or similar discipline
5+ years of professional experience in data science, artificial intelligence, or machine learning
Programming experience in one or more of the following: Python, Julia, R, C, C++, C#, Java
Experience leading technical teams or projects
Advanced degree (Master's or Doctorate) in Data Science, Applied Statistics, Computer Science, Mathematics, or another similar technical background
3+ years of experience in natural language processing
3+ years of experience in SQL or NoSQL Database Languages
Proficient with data visualization tools
Proficient in deep learning frameworks such as PyTorch and TensorFlow
Experience with generative AI models, including LLMs, for building knowledge-driven solutions
Experience integrating models into customer environments, both on-prem and in cloud environments
Experience working in an agile software development team
Experience with MLOps and MLOps tool stack such as ClearML or MLFlow
Experience working in cloud computing environments such as Azure and AWS

Data Scientist

Key skills