Job Description

In this position, you will be working on end-to-end data pipeline implementation from understanding research objectives, data collection using cameras and wearable sensor technology, exploratory data analysis, cleaning and pre-processing of raw data, modelling (using Machine Learning/Deep Learning techniques) and sharing of insights to stakeholders using visualizations. The goal is to find a relationship between qualitative and quantitative data in order to understand passengers\' preferences and improving the passengers\' inflight experience. You will work closely with hardware engineers, design researchers and project manager to successfully collect data from sensors in a cabin stimulator, leverage predictive modelling and provide meaningful insights.

Requirements

• Bachelor\'s or Master\'s degree (preferred) in Data Science, Computer Science, Engineering and Mathematics, Statistics or a related-field
• Applied experience with statistical modelling (hypothesis testing), machine learning (supervised and unsupervised learning techniques) and modern deep learning architectures
• (CNNs, LSTMs).
• Experience with at least one programming language (with a preference for those commonly used in machine learning or scientific computing such as Python or C++)
• Proficient in digital signal processing and data analysis
• Familiar with embedded coding and iOS/Android app development
• Experience exploring, analysing, and visualising data.
• Hands-on experience using PyTorch, TensorFlow, Pandas, NumPy, Sklearn or similar machine learning/scientific libraries.
• Proficient in handling complex requirements and turn into computation logic
• Candidate should like reading documentation and research papers.
• Able to communicate and relay Data Science solutions adequately to business stakeholders.
• Candidate should be comfortable working on multiple projects and in a dynamic environment.
• Candidate should be able to work independently as well as be a team player.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

Times Higher Education