Your Perfect Job Awaits! Data Cleansing / Data Formatting – 100% Work From Home, Day Shift!

Work Schedule:

• Hours: Day shift! Part-time (minimum 2 hours per day)
• Pay: PhP 200 per hour
• Location: Anywhere in the Philippines – work from home, remote, or province
• Work Type: 100% Work From Home

About the Work:

Are you an experienced Data Cleansing / Data Formatting specialist looking for an exciting new career opportunity with a work-from-home lifestyle? Join a leading data science organization and take advantage of this excellent opportunity. We connect top talent with top companies, and this role is perfect for individuals passionate about advancing their careers, gaining international experience, delighting our client, and enjoying the benefits of working from home.

About the Company:

Our client is a leader in their field, dedicated to providing exceptional services to their clients. They value innovation, efficiency, and client satisfaction and understand the crucial role this position plays in achieving their objectives.

Duties and Responsibilities:

• Data Review and Validation: Examine data for accuracy, consistency, and completeness. Identify and correct errors or inconsistencies.
• Data Cleansing: Remove duplicate records, standardize data formats, and rectify inaccuracies in datasets.
• Data Formatting: Convert data into a standard format suitable for analysis or reporting. Ensure data is organized and structured according to project requirements.
• Data Integration: Merge data from various sources into a unified format and ensure compatibility.
• Documentation: Maintain detailed records of data cleansing processes, methodologies, and changes made.
• Quality Assurance: Implement and follow data quality standards and practices. Conduct regular audits to ensure data accuracy.
• Collaboration: Work with other teams, such as data analysts, data scientists, or IT departments, to understand data requirements and address issues.
• Reporting: Generate and present reports on data quality, cleansing progress, and formatting results.
• Troubleshooting: Identify and resolve data-related issues or anomalies. Provide solutions to improve data quality.