Data Scientist

Resbonsibilities

• Facilitate discussions with stakeholders to understand their business challenges, sharpen the business use cases and translate them into data science projects.
  
  
• Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping.
  
  acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life.
  
  
• Technical assessment on the maturity, viability, and suitability of Al research, technologies and trends that are relevant to the industry.
  
  
• Present findings, solicit feedback and prioritise refinements to the analysis in close iteration with stakeholders while managing overall project timeline.
  
  
• Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle.
  
  
• Transfer technology to industry partners.
  Technical engagement and collaboration with research institutes and institutes of higher learning.
  
  

Requirement

• Postgraduate or Ph.D. Background in engineering, computer engineering, computer science, mathematics, statistics or equivalent.
  
  
• Strong technical knowledge in Al, specifically in Computer Vision (CV), Natural Language Processing (NLP), recommendation system and/or Synthetic Al.
• Good understanding of the latest research and technologies in Al for production, including deployment to mobile handsets and IOT devices.
  
  
• Proficient in building machine learning models to identify, recognise patterns and make predictions.
  
  
• Strong coding experience in programming languages such as Python, C++.
  
  
• Hands-on experience with one or more deep learning frameworks, e.g.,
• TensorFlow, Torch.
  
  
• Experience in model deployment.