Job Description

In this position, you will be working on end-to-end data pipeline implementation from understanding research objectives, collecting data using cameras and wearable sensor technology, exploring methods of data analysis, cleaning and pre-processing of raw data, modelling data using Machine Learning/Deep Learning techniques, and sharing of insights to stakeholders using visualizations. Our research aims to understand passengers’ sitting behaviours and preferences on a flight so as to improve their in-flight experience. Your key role includes gathering data from sensors in a cabin simulator, leveraging on predictive modelling, and providing meaningful insights. In your day-to-day, you will be working closely with engineers, design researchers, and the project manager.

Requirements

• Bachelor's or Master’s degree (preferred) in Data Science, Computer Science, Engineering, and Mathematics, Statistics or any 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)
• Proficient in digital signal processing and data analysis
• Familiar with embedded coding and iOS/Android app development using Kotlin, Java, XML
• 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 be in a dynamic environment.  
• Candidate should be able to work independently as well as be a team player.
• Candidate is required to conduct research studies. 
• Must be willing and able to conduct research studies on weekends.