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.

Qualifications:

To qualify, you must have
- 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.

Ideally, you’ll also need 
- 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