Company Description
Fipsar Inc is a data management and analytics consulting company that builds, maintains and activates every layer of the data stack for life sciences and healthcare organizations — from establishing a strong data platform to improving how decisions are made with AI and machine learning. Founded in 2010 and headquartered in Hillsborough, NJ,
Role Description
- This is a full-time hybrid role for a Data Steward at Fipsar Inc.
- Data Steward performs data stewardship operations using Veeva Network, Veeva Open Data and Veeva CRM.
- Ensure high quality HCP/HCO data is collected, verified and maintained.
- Design, document and optimize processes to ensure best-in-class delivery of data quality
- Continuously collect, enter, organize, verify, and update customer information through multiple channels such as telephone and Internet.
- Establishes good working relationships with business owners, and supporting the governance structure to ensure on-going data accuracy and completeness
- Data processing, data analysis, and data quality inspection
- Submit and manage change requests directly from Veeva CRM
- Identify duplicate, inactive, outdated, and incomplete records
- Helps clients better manage their customer master data (doctors and hospitals) to improve data quality. To be able to do so, Data Stewards contact Health Care Organisations / Health Care Professionals (HCOs / HCPs) to verify profile information.
- Proactive maintenance of existing data and handling customer requests
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Qualifications
- 4-6 years’ experience as data steward, data analyst, or business analyst
- Hands-on experience in Master Data Management (MDM)
- Bring deep business understanding of pharmaceutical industry and data standards with domain experience in Pharma Marketing and Sales
- Knowledge of medical terminology and data quality standards within the life sciences industry
- Good at communication, strong logical thinking, and language expression skills
- Competency in: understanding and correcting data discrepancies; reading and translating data models; data querying; identifying data anomalies and root cause analysis;
- Knowledge of SQL and the ability to query relational databases preferred