PRIYA DAULATBAZI

• Reviewed and processed credentialing applications to ensure accuracy, completeness, and compliance with all accreditation standards.
• Conducted research into industry best practices for data management processes and procedures.
• Coordinated with internal departments such as medical staff services or risk management to resolve any issues identified during the verification process.
• Processed re-credentialing applications for existing providers according to contractual requirements.
• Conducted thorough background checks and verified educational and professional qualifications.
• Maintained up-to-date records of credentialing statuses in database systems.
• Managed communication between providers and external organizations regarding licensing requirements and updates, renewals of licenses, certifications.
• Analyzed medical staff data to ensure compliance with applicable regulations.

● Project AdWords: Managed at least 20 calls per day with stakeholders, Business key people, Sponsors to understand about payment processes for ads, determining payment validity for the last 90 days or all-time mode.

● Key Result Areas: Prepared daily, weekly, and monthly reports on performance, productivity, error rate, and quality.

● Root Cause Analysis: Conducted RCA for errors, tracked performance, and shared insights with the Team Lead.

● Quality Analyst: Worked on revenue segmentation in the Global Ad Market.

● Special Projects: Handled projects like AppDev, Merge, Google Mapping, and SOW Project and Google Ads.

● Customer Experience: Respond the customer queries via email, phone, messages and resolving issues efficiently and effectively

● Overall Customer satisfaction: 98 Percent customer satisfaction rating for right delivery of solution.

● Manage to train new hires, trainees for customer service protocols, policies, approach for Root Cause Analysis, approach to maintain professionalism demonstrating real life criterias

• Projects: Coordinated, scheduled, and executed in-depth data entry projects.
• Review: Reviewed customer data to identify and address discrepancies.
• Data Analysis: Analyzed customer data to ensure accuracy of information.
• Databases: Analyzed large datasets to identify trends, patterns and correlations for business insights.
• Defined KPIs based on collected data sources.
• Tools: Utilized advanced analytics tools such as SAS, SPSS, Excel PowerPivot, to manipulate large volumes of structured and unstructured data sets.