Assistant Manager, NUHS Academic Informatics Office

Location: Singapore
Discipline: Business Operations
Job type: Permanent
Contact email:
Job ref: 268417
Published: over 1 year ago
At NUHS Academic Information Office – Management Decision Support Office, we support the organisation in drawing meaningful insights and develop automated data products from healthcare data. You are to assist in the development of strategic cluster wide and institution specific projects. You will have the opportunity to develop a suite of skills from gathering business requirements to the deployment of machine learning models.

Job Responsibilities
You will be responsible for the following:
  • Develop effective analytical and data science solutions to improve cluster-wide and institution specific healthcare milestones
  • Collaborate and establish strong relationships with key stakeholders, programme and cross-functional teams and the management to prioritize information needs
  • Work closely with other technology, engineering, finance and operations teams to build analytical and data science solutions
  • Develop end-to-end data modeling cycle from gathering business requirements to model deployment
  • Translate clinical and operational needs into data-driven solutions
  • Derive meaningful insights and foresight from large datasets, convey the analysis and provide feedback to align programmes
  • Guide juniors in end-to-end data modeling cycle, interpretation and communication of data and analysis of results
  • Minimum Master’s degree in Computer Science, Information Systems, Analytics, Statistics, Mathematics, Industrial Engineering, Health Informatics or related fields
  • Minimum 2-3 years of job experience in data analytics, statistics or data science environment
  • Good interpersonal skills, a detail-oriented and flexible person who can work across different areas within the team as well as align cross functionally outside the team
  • Ability to deliver clear, concise reports and presentations/dashboards and effectively articulate observations and recommendations
  • Proficient in the use of data science programming languages (e.g. Python, R and SQL)
  • Familiar with Classification, Regression and Clustering machine learning libraries (e.g. scikit-learn)
  • Proficient with Data Visualization & Management Tools (e.g. Tableau) and/or Commercial Statistical Software (e.g. SAS, SPSS, STATA) in building reports and dashboards
  • Knowledge of state-of-the-art machine learning algorithms (e.g. Ensemble models, Attention), probabilistic models (e.g. MCMC) and understanding of data science/machine learning pipeline is preferred
  • Familiar with database management, architecture design, system integration, security and data governance is preferred
  • Ability to build and interpret probabilistic models of complex, high-dimensional systems is preferred
  • Knowledge of natural language processing libraries (e.g. NLTK, Gensim, SpaCy, Huggingface, fairseq) and/or deep learning frameworks (e.g. Pytorch, Tensorflow) is a plus
  • Familiar with Git commands and Unix/Linux system experience is a plus
  • Experience with deployment of machine learning models is a plus
  • Experience with formulating and solving OR models like linear (large-scale), mixed integer, non-linear and evolutionary programming methods and libraries (e.g. CPLEX, Gurobi, Optaplanner) is a plus
  • Can-do attitude and ability to work independently, comfortable with ambiguity