Key Responsibilities:

Data Cleansing: Cleanse and preprocess diverse datasets to ensure accuracy, consistency, and completeness. Identify and rectify errors, inconsistencies, and outliers in the data to enhance its quality.

Data Validation: Develop and implement validation procedures to verify the integrity of the data. Collaborate with other team members to cross-verify information from various sources and resolve discrepancies.

Quality Assurance: Implement quality assurance processes to maintain high data quality standards. Regularly monitor and audit the cleansed data to identify potential issues and take corrective actions.

Collaboration: Work closely with other data scientists, researchers, and volunteers within QUTII. Collaborate on data-related projects, share insights, and contribute to the overall improvement of data quality and accuracy.

Documentation: Document data cleansing processes, methodologies, and findings. Maintain clear and comprehensive records of changes made to the datasets and report progress to the project lead.

Continuous Improvement: Stay updated with the latest techniques and tools in data cleansing and preprocessing. Continuously explore innovative approaches to enhance the efficiency and effectiveness of data cleansing processes.

Adherence to Ethics: Ensure adherence to ethical guidelines and data privacy regulations while handling sensitive information. Uphold confidentiality and security standards when working with data.