Associate Engineering Data Scientist

Position Responsibilities

• 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.

Basic Qualifications

• Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement.
• 2+ 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.

Preferred Qualifications

• Advanced degree (Master's or Doctorate) in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement.
• 1+ years of experience in natural language processing.
• 1+ 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.