Household, Income and Population Intern

Modernising Administrative Data Processing for Household income and wealth data The Income Statistics Section uses individual level administrative data from multiple sources to compile data on household income and wealth. As data received from different sources are in varying formats and structures, transformation and processing are needed to standardise and prepare the data for efficient compilation and analysis. This project aims to modernise and streamline these processes through the development of an open-source data processing pipeline. Responsibilities 1. Analyse existing processing requirements (currently detailed in SAS programs) and translate them into efficient, well-structured open-source codes (in Python language) 2. Design and develop modular, multi-stage workflows and automation processes to ingest, validate, transform and standardise datafiles of different formats, layouts and structures. 3. Develop automated processing and quality assurance checks to improve efficiency, consistency and reproducibility of data preparation. 4. Establish a Git repository with appropriate version control practices, documentation and code organisation to support collaborative development and maintenance. Through this project, the intern will gain an understanding of the processes involved in producing household income and wealth data and the opportunity to apply programming skills and build pipelines on real-world data. Requirements - Knowledge or experience in computer science, data engineering, data processing, or process automation. - Proficiency in Python and able to apply best practices in coding - Process automation and data analytics - Interest in problem solving, with a curiosity and willingness to learn - Able to work independently and detail-oriented Internship Period: 5-6 months, from Feb 2027 to Jun/Jul 2027 Part-time option available: Minimum commitment of 3 days per week