Job Description

Short Description This position supports the University to implement data-driven decisions by executing analytics projects with relevant stakeholders that cover all tasks in the various phases of the CRISP-DM framework. He/she also supports trainin Short Description This position supports the University to implement data-driven decisions by executing analytics projects with relevant stakeholders that cover all tasks in the various phases of the CRISP-DM framework. He/she also supports training and assists in other matters to contribute to the effective and efficient functioning of the Business Intelligence and Analytics department. Design analytics projects to meet specified objectives Carry out data preparation, including cleaning, transforming, validating and exploring data Build, diagnose, validate, and improve the performance of analytics models to support decision making Collaborate with relevant stakeholders to develop and deploy analytics findings and models Develop BI reports and dashboards to facilitate the translation of the analytics Communicate the findings and make recommendations to the relevant stakeholders Prepare reports/papers and handle other administrative tasks Prepare presentation materials and make presentations to relevant stakeholders Organise and provide training to the Schools and other departments in SUSS Keep abreast of latest developments in analytics and subsequently ideate and implement the methodologies to solve potential business problems Contribute to the efficient and effective functioning of BI&A Job Requirements A good undergraduate or graduate degree in a relevant quantitative field (e.g., Mathematics, Statistics, Business Analytics, Data Science) from a recognised University Minimum of 3 years of work experience in a relevant position. Fresh graduates will also be considered. Possess strong knowledge of methodologies applied in dashboarding, statistics and data mining. In particular, knowledge of association analysis, clustering, regression, decision trees, neural networks, etc.). Knowledge of time series forecasting, text mining and/or optimisation is advantageous. Proficient in the use of at least two of the following software/programming language for data mining and statistics: SAS, SPSS Modeler, SPSS Statistics, R, Python etc. Proficient in the use of at least one of the following dashboard software: Power BI, Qliksense or Tableau. Proficient in the use of MS Excel, Word, and PowerPoint Familiarity with programming languages such as Python, R or SAS is advantageous. Mature, meticulous and possess high level of ethics and integrity Effective interpersonal skills with excellent command of written and spoken English Resourceful team player who is able to work independently and display initiative Ability to communicate well so as to act as liaison and help reach out to stakeholders, such as faculty and admin staff from other departments and divisions as well as associates and other stakeholders