Business Statistics Intern

Redesigning the Statistical Imputation Process for Industry Statistics Attached to the Business Statistics Division, you will contribute to the redesign of the statistical imputation process for industry statistics of the services sector. This project aims to enhance the robustness, flexibility, and scalability of the imputation framework by leveraging administrative data and the latest statistical methodologies. Responsibilities - Collaborate with a multidisciplinary team to understand business and technical requirements for the statistical imputation process, with a particular focus on integrating administrative data to improve the estimation of detailed data items. - Design and develop a modular and scalable imputation framework that is adaptable to new data sources, evolving data structures and business needs, ensuring long-term maintainability and extensibility. Requirements - Knowledge or experience in data science, data analytics, statistical analysis, or computer science. - Proficiency in Python is essential. Experience with data manipulation, database management, and statistical or data science libraries (e.g. pandas, NumPy, SciPy, scikit-learn) will be an advantage. - Strong analytical and problem-solving skills. - Meticulous, organised, and detail-oriented, with the ability to work effectively with large, complex datasets. - Self-motivated and able to work independently, with good time management skills to deliver quality outcomes within established project timelines. Internship Period: 6 months, from Jan to Jun 2027 (flexible start and end dates)