Data Scientist

Key Responsibilities
. 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 AI research, technologies and trends that are relevant to the industry
. Develop software components based on microservices-based architecture
. Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle
. Propose, implement, and validate algorithms, ensuring functional and non-functional requirements such as transparency, fairness, scalability, security, integration complexity and operational costs
. Write thought leadership articles, including blogs and papers, on AI
. Transfer technology to industry partners.
. Technical engagement and collaboration with research institutes and institutes of higher learning.

Requirements:

1. Background in engineering, computer engineering, computer science, mathematics, statistics or equivalent

2. Strong technical knowledge in AI, specifically in Computer Vision (CV), Natural Language Processing (NLP),
   recommendation system and/or Synthetic AI

3. Good understanding of the latest research and technologies in AI for production, including deployment to
   mobile handsets and IOT devices.

4. Strong coding experience in programming languages such as Python, C++

5. Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch

6. Team player with the ability to work in a cross-functional team with excellent interpersonal skills.

7. Strong communication skills, both verbal and written, as well as strong presentation and engagement skills

8. Strong stakeholder management skills.