Data Scientist
Remote | London
Volunteer
3 Months | 15h /week
About Us
"At TiiQu, we're on a mission to revolutionize how individuals access knowledge about the environment. Our groundbreaking QuTii project aims to empower everyone with the truth and understanding they need to become eco-conscious change-makers. We are fueled by a commitment to sustainability, innovation, and preserving our planet for generations to come.
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Who are we looking for
About the Role
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.
Required Skills & Experience
Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
Strong proficiency in data cleansing techniques, data preprocessing, and data validation.
Experience with data cleaning tools and software packages (e.g., OpenRefine, Trifacta, pandas in Python).
Familiarity with programming languages such as Python, R, or SQL.
Excellent attention to detail and analytical skills.
Ability to work independently and collaboratively in a team environment.
Passion for contributing to a non-profit initiative and making a positive impact on global knowledge dissemination.
Benefits and proof of work
Your efforts will not go unnoticed. You will receive a letter of recommendation and we'll be glad to offer references when needed.
Other benefits:
Enjoy remote work and flexible hours for a balanced life.
Leverage tasks by skills, boosting expertise and teamwork
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