Principal Applied Scientist

Overview

Looking for a diligent and accomplished Principal Applied Scientist with a keen eye for detail to work directly with our engineering teams and carry G42’s new age AI-driven products & solutions from conceptualization, planning & prototyping all the way to testing & delivery.

Responsibilities

Functional:

• Take new technologies from early concept to product level while iterating & prototyping and ensuring that the system predicts accurate & stable results.
• Conduct in-depth data analyses, propose relevant optimization models & algorithms, and carry out proof of concept trials (PoCs) according to client needs.
• Improve accuracy of models/algorithms to solve problems encountered during the implementation.
• Coordinate various teams to solve these problems in an efficient and cost-effective way.
• Propose scenarios where AI techniques could improve the efficiency of client businesses.
• Provide pre-sales and post-sales technical support to the business development team.
• Invent, analyze, design, develop and optimize algorithms for G42 Smart Nation’s range of platforms and solutions.
• Analyze complex datasets to make insightful and relevant decisions regarding real-world applications.
• Design, develop and conduct in-depth research projects.
• Implement models & algorithms to enhance and upgrade existing systems, processes, and products.
• Oversee all data analysis and generate visualizations.
• Use modeling, simulation and optimization to design processes, algorithms, and prediction/classification systems.
• Assess the feasibility of new approaches to business problems through experiments and research.
  
  

• Master’s Degree in Computer Science, Computer Engineering or Machine Learning
• 4+ years' experience in AI and Machine Learning algorithm development
• Python experience of at least three years, with usage within the last two years
• Hands-on experience with AI frameworks (TensorFLow, PyTorch, Keras)
• In-depth understanding of machine learning techniques, such as SVM, Decision Tree, Markov Chain, graph analysis (e.g. probabilistic graph model), etc.
  
  

• Outstanding problem-solving and analytical abilities
• Excellent written and verbal communication skills
• Demonstrated experience in collaborating with cross-functional teams
• Hands-on experience with CV/ML libraries such as OpenCV, scikit-learn, VLFEAT, Pillow Experience
• In-depth knowledge of the latest developments in AI and machine learning