Consumer Price Index Intern (NOVA)

NOVA: Non-cooked Food Data Orchestration, Validation and Automation For the compilation of Non-Cooked Food (NCF) CPI, Prices Division obtains electronic price data from various supermarket chains on a monthly basis and conducts bi-weekly field surveys for prices of perishable items at wet markets. Following which, the data are validated and processed before compilation. The intern is expected to support the development and implementation of automation solutions for Non-Cooked Food CPI data processing. Responsibilities (1) assisting with extracted OCR-based data cleaning/transformation, (2) integrating datasets from multiple sources to prepare consolidated summary on price changes (3) incorporate automated data cleaning/validation techniques to improve workflow e.g. outlier detection by comparing price data across various data sources, verifying data quality, e.t.c. (4) preparing dashboards on key insights/trends on NCF (5) assisting in data analysis and generating statistical outputs such as 'Shrinkflation' statistics The intern is expected to contribute to the development of web-scraping scripts, ML and LLM scripts to leverage on the latest digital tools to compile and process data more efficiently. Requirements - Knowledge or experience in computer science, data science, artificial intelligence, machine learning, or data analytics. - Knowledge in open source tools such as Python, R, and experience working with Machine Learning (ML)/AI models is beneficial. Internship Period: 6 months, from Jan to Jun 2027 (flexible start and end dates) Part-time option available: Minimum commitment of 3 days per week