Senior Manager, Office of the Provost (PVO) (Educational Data Scientist)

Job Responsibilities:

• Collect and pre-process data from various sources, such as student records, assessments, feedback and learning analytics.
• Analyse and interpret data to discover patterns, trends and insights that can inform educational decisions.
• Design, Develop, Deploy, Upgrade and Maintain software solutions. These solutions should be data driven, may involve classical machine learning techniques (decision trees, SVM) and recent techniques for LLM models (LangChains). For example:
• A system to recognize / summarise prior learning of students based on the profiles/evidence collected and map it to the competencies of relevant courses.
  • Design and deploy algorithms and models to analyse student evidence and identify relevant competencies.
  • Collaborate with module leads and instructors to ensure accurate mapping of prior learning to course competencies.
  • Continuously improve and update the recognition system based on feedback and evolving industry standards.
• Prediction models for student success and identify students at risk of falling behind.
  • Utilize machine learning and statistical techniques to analyse student data and develop predictive models for academic success.
  • Identify key indicators and risk factors that contribute to student success or at-risk behaviours.
  • Collaborate with academic advisors and faculty members to implement intervention strategies for at-risk students.
• A system to analyse student feedback to teachers and courses using AI techniques and provide actionable recommendations.
  • Develop natural language processing (NLP) models to analyse student feedback and sentiment towards instructors and courses.
  • Identify common themes and patterns in student feedback to gain insights into areas for improvement.
  • Provide data-driven recommendations to faculty and administrators to enhance teaching methods and course content.
• Collaborate with educators, researchers, and stakeholders to understand their needs and requirements to deliver actionable insights.
• Collaborate with cross-functional teams (e.g., faculty, administrators, researchers, and other stakeholders)
• Communicate findings, insights, and recommendations to stakeholders in a clear and concise manner.
• Collaborate with academic coaches to advise students on development of portfolio in fields related to IT and data science.
• Work with vendor when necessary to develop larger system after selected pilot projects.

Job Requirements: 

• Bachelor’s or master’s degree in a relevant field (e.g. Computer Science, Engineering, Data Science, Statistics or related disciplines)
• Experience in developing and implementing data-driven solutions in an educational or learning environment.
• Experience in data collection, pre-processing, and analysis
• Knowledge of machine learning algorithms, statistical analysis, and data visualization techniques.
• Proficiency in programming languages, such as Python and R, for data analysis and modelling
• Familiarity with natural language processing (NLP) techniques for text analysis and sentiment analysis.
• Experience with large language models and related frameworks
• Knowledge of vector databases and embeddings to store and retrieve data from various sources, such as student records, assessments and feedback is a plus.
• Knowledge of AI and machine learning techniques and algorithms, such as regression, decision trees or neural networks.
• Knowledge of educational theories and practices, such as competency-based learning, learning analytics or feedback analysis is an advantage.
• Excellent communication skills, with the ability to effectively convey complex concepts to both technical and non-technical stakeholders.
• Strong problem-solving skills and ability to work independently as well as collaboratively in a team-oriented environment.
• Attention to detail, with a commitment to delivering high-quality and accurate results.