{"@context":"https://schema.org/","@type":"JobPosting","title":"Data Analyst","educationRequirements":{"@type":"EducationalOccupationalCredential","credentialCategory":"bachelor degree"},"experienceRequirements":{"@type":"OccupationalExperienceRequirements","monthsOfExperience":36},"description":"

Hours:\tDay shift! Part-time (minimum 2 hours per day)

Pay: \tPhP 200 per hour

Location: \tAnywhere in the Philippines; work from home, remote or province

Work type: \t100% Work From Home

About the Work

Are you an experienced Data Cleansing / Data Formatting seeking a new and exciting career opportunity with a work at home lifestyle? I have an excellent opportunity for you to join a leading organization. I connect top talent with top companies, and this role is a perfect match for individuals passionate about advancing their career, gaining more international experience, delighting my client and enjoying the benefits of a work at home lifestyle.

About the Company

My client is a leader in their profession, committed to providing exceptional services to their clients. They value innovation, efficiency, and client satisfaction, and they understand the vital role that this important role plays in achieving these 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.

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