
JAC Group
About the job
Overview
Our client, a telecommunication company in Hong Kong, is looking for a Data Scientist/Senior Data Scientist to work together for expanding business units.
Job Responsibilities
- Getting involved in data scientist team to develop modeling techniques and data science capabilities, supporting Lead Data Scientist on data related works.
- Analyzing large datasets by using data science tools and techniques to find trends and patterns on business perspective.
- Mining big datasets by utilizing algorithms and models, guaranteeing data accuracy and uniformity.
- Identifying and collecting relevant data sources for business needs, implementing improvements to operational systems.
- Working closely with IT team and engineering team for the development of data products.
- Assisting non-technical departments within the business in explaining the usages and benefits for business performance of data science. Communicating with stakeholders for analytic solutions.
Job Requirements
- Master’s degree or PhD in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field. An equivalent of the same in working experience is also acceptable for the position.
- 3+ years of working experience in a data science capacity. Experience in Retail/FMCG/Property/Telecom is a plus.
- Proficiency with data mining, mathematics, and statistical analysis, comfortable with analyzing and manipulating large, complex, high-dimensional data from numerous sources.
- First experience of Deep Learning projects: NLP/computer vision, neural network. Advanced pattern recognition and predictive modeling experience.
- Coding abilities at least one of the following languages: Python and R.
- Experience working in a cloud environment such as AWS, Azure or GCP.
- Working proficiency level of Cantonese is needed. (Speaking, listening and writing)
Personal data collected will be used for employment-related purpose only. We regret to inform that only shortlisted candidates will be notified, thank you.