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Senior Analyst with 6+ years in data acquisition, processing, and quality assurance.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Skilled Data Specialist with more than 4+ years of industry experience in collecting, organizing, interpreting, and disseminating various types of dataset figures. Creative in finding solutions to problems and determining modifications for optimal use of organizational data. Organized and timely in providing staff, departmental members, and executive management with reports on specific data findings and their impact on organizational growth and success.
Veerayatan Institute of Engineering
B.E. Mechanical · Mechanical
January 1, 2015 – January 1, 2019
Catalyst Partners
Data Research Analyst
February 1, 2024 – Present
Ahmedabad, Gujarat, India
NielsenIQ
Sr. Data Processing Specialist
July 1, 2020 – February 1, 2024
Vadodara, Gujarat, India
BAU Process
June 1, 2021 – February 1, 2024
Responsible for the BAU production and maintenance for PepsiCo deliverables along with that executing client inquiries and change requests for the western European countries.
Global Database Setup
April 1, 2021 – June 1, 2021
Have completed the setup of the new database for the countries Poland and Romania as per the client production order.
Cultural Fit Analysis
The candidate's experience across different companies (NielsenIQ, Catalyst Partners) and roles (Sr. Data Processing Specialist, Data Research Analyst) suggests adaptability. Involvement in global database projects and training freshers indicates a collaborative mindset. The projects listed, while not highly diverse in technology, show a consistent focus on data operations and client delivery.
Soft Skills & Operational Fit
The candidate demonstrates experience in client interaction, problem-solving for data-related queries, and training, indicating good operational fit for roles requiring client focus and team collaboration. The resume highlights responsibility and a proactive approach to improving data quality.