Data Scientist/ Senior Data Scientist - DFS91121147 in Hong Kong at DFS

Date Posted: 7/16/2021

Job Snapshot

Job Description

The Data Scientist team is responsible for building, expanding, and maintaining the Company’s algorithmic assets within one of the pillars of the Artificial Intelligence (AI) team. The incumbent needs to have a strong knowledge of AI/Data Science concepts and for building various data science models independently and providing expertise to other teammates. Working closely on a variety of business cases the incumbent will help generate significant and recurrent returns from the algorithms in place and explore new use cases and develop new AI capabilities.

Key Responsibilities:

• Grow the organisation’s AI capability around personalisation problems such as recommendations and customer profiling.
• Identify business opportunities, solve problems, and translate technical concepts into clear and actionable insights for business and enterprise leaders.
• Help conduct trainings, educate stakeholders, and hold workshops to build up in-house data science capabilities.
• Lead projects to achieve business objectives, taking ownership of end-to-end model development and deployment.
• This role will require end-to-end development of AI models, including deploying it into production.

Key Requirements:

• Bachelor/Masters in computer science, data science, statistics, mathematics, or equivalent fields.
• 3-5 years relevant working experience.
• Knowledge in deploying end-to-end ML/AI solution in the cloud. Strong knowledge in data science concepts and programming languages such as SQL, python and java preferred.
• Strong project management and organizational skills.
• Excellent written, verbal communication skills and adept at engaging various stakeholders.
• Expert in programming languages in SQL & Python and java preferred.
• Expert in manipulating data sets with structured and unstructured data.
• Experience in using machine learning libraries such as Scikit-learn, Tensorflow, Keras, Pytorch, etc. Experience in deploying production level ML solution in the cloud. Strong understanding of cloud data infrastructure technologies (e.g. Databases, Spark, Tensorflow, etc).