Data Science Manager - DFS91121146 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:

• Lead the data science team, building roadmaps to achieve business objectives and taking ownership of model development and deployment.
• Mentor and grow the technical capabilities of the data science team.
• First point of contact for DFS regional data science team.
• Advocate, work and collaborate with other teams to increase adoption of AI.
• 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.

Key Requirements:

• Bachelor/Masters in computer science, data science, statistics, mathematics, or equivalent fields.
• 6-10 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).