Associate Principal/Senior/Analyst, Data Science, Group Finance Analytics

4 days ago

Singapur, Singapore Singapore General Hospital Full time

You will champion the development of new data science techniques, methodologies and delivery of analytics projects from planning through to prototyping, testing, implementation and publication. You will identify and develop core data science components for the delivery of projects, construct dedicated databases and computing environments, and explore and visualise complex data sets to provide business insights. As a key member of the Value Driven Analytics Research (VADAR) initiative, you will provide technical expertise to researchers’ data needs, and/or RFPs and related commercial activities. Your duties include working on data analytics projects that are commissioned by institutions within SingHealth and provide recommendations based on the clinical, operational and financial analysis performed. You will collaborate with various stakeholders and cross-functional teams, especially the value/bundle care, population health, clinical quality and finance offices within the cluster.

For the Senior Analyst position, you will also guide and mentor lower-level team members and are expected to influence key stakeholders, spearheading a data-driven approach to contribute to research breakthroughs.

Other responsibilities include projects as and when assigned.

Requirements:

  • Bachelor’s Degree in Finance, Statistics, Mathematics, Computer Science/ Engineering, Business Analytics or other quantitative disciplines with preferably 2 to 5 years of relevant experience
  • Advanced theoretical understanding of statistical modelling, machine learning, developing simulation models
  • Experience with algorithms and coding proficiency with tools such as R/ Python/ SQL
  • Good understanding of MATLAB, SPSS, and STATA
  • Meticulous and possesses strong analytical and problem-solving skills
  • Excellent verbal and written communication skills
  • A team player who is also able to work independently in a fast-paced environment
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