Digital Flight Data Analyst - Intern

This internship offers a unique opportunity to contribute to the development of cutting-edge tools in aviation safety and data analysis, leveraging the power of Machine Learning. Your mission for this internship is to develop an interactive tool for mapping Flight Data Recorders parameters based on Systems and subsystems. To excel in this internship, you will need to become familiarized with the system-wide functionality of Airbus aircraft. Your tasks will include codifying the potentially-affected parameters for a given incident to map the fault propagation tree, conducting research on, and ultimately implementing, the most appropriate Machine Learning algorithm(s) for this particular time-series application, as well as building data visualization and user-interface tools. By the end of this internship, you will have delivered a robust tool that provides an exhaustive list of FDR parameters along with a practical representation of how and what all systems are impacted with respect to a particular fault. Additionally, you will have provided a first-order proof of concept of the applicability of Machine Learning techniques in this space as demonstrated by a limited-scope use case. Required Skills: - Strong programming skills in Python. Knowledge of key machine learning libraries (Scikit-learn, Tensorflow) and scientific computing libraries (e.g., SciPy) is an asset. - Experience with Machine Learning (ML) for time-series applications, including exposure to supervised and unsupervised learning algorithms, an understanding of data preprocessing, feature engineering, and data visualization methods. - Experience with data visualization libraries (e.g., Matplotlib, Plotly, D3.js). - Familiarity with UI/UX design principles for intuitive interfaces would be a plus.,