Data Expert

4 days ago


Kuala Lumpur, Kuala Lumpur, Malaysia Kantar Group Full time
Job Description

This role is a key part of the MyWorldpanel (MWP) Rollout Program, focusing on validating data transformation processes and implementing quality control procedures. As a member of our cross-functional team, you will collaborate closely with senior regional stakeholders to ensure seamless integration of data across various datasets.

You will work with the regional client delivery team to define a streamlined model for migration to MWP, ensuring accurate and reliable data insights. Your expertise in data analysis, collection, and visualization will be essential in driving business decisions and strategies.

Key Responsibilities:

  • Gather and Integrate Data: Collect data from multiple sources, including the current production system and MWP, ensuring consistency and integration across various datasets.
  • Ensure Data Accuracy: Organize and validate data to ensure accuracy, completeness, and reliability for actionable insights.
  • Data Analysis for Validation: Analyze datasets to identify relevant data points and slices for validation. Provide detailed explanations for significant discrepancies or variances found in the data.
  • Adaptation of New Methodologies: Stay informed of new data methodologies and their potential impacts on business processes. Recommend data adjustments and improvements where necessary.
  • Support Regional Teams: Work closely with regional teams to determine the best approach for transforming itemization in attribution. Suggest and implement reporting methods or models to improve the data collection and reporting process.

Reporting and Analytics:

  • Develop Reports and Dashboards: Create clear, insightful reports and interactive dashboards for data comparison and analysis.
  • Effective Data Visualization: Leverage data visualization tools to present complex data in an easily understandable format for non-technical stakeholders.
  • Cross-Team Collaboration: Collaborate with regional and central teams to define effective methods for comparing data, identifying trends, and monitoring business-as-usual operations.
  • Audit and Data Correction: Audit data from different regions to identify and correct inconsistencies, ensuring high data quality.
  • Data-Driven Decision Support: Provide recommendations and insights based on data findings to help guide business decisions and strategies.

Quality Assurance and Data Management:

  • Ensure Data Consistency: Implement and oversee processes to maintain data integrity and consistency across all sources and platforms.
  • Implement Data Validation Processes: Ensure that robust data validation practices are followed, reducing errors and ensuring the quality of data in reporting.


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