Senior Data Scientist

1 week ago


Hong Kong, Central and Western District, Hong Kong SAR China Gravitas Recruitment Group Full time

Position overview

Support the end to end project with your team member data scientist: from understanding the business requirements to the delivery.

Working on complex data science/analysis projects, you will also work on new PoC and R&D projects to anticipate the business needs. It will be your responsibility to support guiding of the stakeholders on the right data transformation approach, creating the models and using the tools you have. You also collaborate with product design and engineering to develop an understanding of needs, and enable smarter business processes-and implement analytics for meaningful insights

Key responsibilities

  • Lead data scientist team members in the development of new insights, advanced modeling techniques, and data science capabilities. Execute analytical experiments methodically to help solve various problems and make a true impact across business units and external partners.
  • Establish actionable KPIs and success metrics and ensures that there is timely and accurate reporting. You will leverages data science tools and techniques in analyzing large data-sets that will enable the development of custom models and algorithms to uncover insights, trends, and patterns in the data, Devise and utilize algorithms and models to mine big data sets, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy
  • Work closely with the IT team for the purpose of facilitating easy and effective access to computing and data resources within the business. Support Lead Data Scientist to identify and integrate new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products
  • Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets. Partner with other non-technical departments within the business assisting them in understanding how data science can benefit them and improve their effectiveness and performance. Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems

Skills and Qualifications

  • A 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.
  • 5+ years of working experience in a data science capacity. No preference for the background sector but a first experience in Retail/FMCG/Property/Telecom is a plus. You will also have a demonstrated and successful experience leading a data science team through the implementation of new data science models, tools, and techniques that lead to improvement if business performance due to a continued culture of informed decision-making. Strong technical understanding of Martech, personalization and marketing automation is preferred.
  • Extensive experience solving analytical issues through quantitative approaches and machine learning methods as well as vast experience using advanced statistical methods, data mining techniques, and information retrieval. A suitable candidate will show comfort analyzing and manipulating large, complex, high-dimensional data from numerous sources. Proficiency with data mining, mathematics, and statistical analysis. Advanced pattern recognition and predictive modeling experience
  • Excellent communication skills in order to be able to tailor and convey technical messages in a clear and understandable manner, leading to business-wide improvement of data management, informed decision making, and ultimate improvement in performance.
  • First experience of Deep Learning projects: NLP/computer vision, neural network. Coding abilities at least one of the following languages: Python and R
  • Experience working with distributed computing tools such as Hadoop as well as experience working in a cloud environment such as AWS, Azure or GCP.

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