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The Associate – MDM will be part of the GCO Commercial Data Management team at the Amgen Innovation Center in India. This role will support the day-to-day operations of Amgen’s core commercial MDM platform and data stewardship activities across key domains (Provider, Payer, Product, Patient, and Consent). The Associate will work closely with senior team members in India and partners in the US/O-US to ensure high-quality master data, accurate documentation, and smooth execution of MDM processes that enable analytics, reporting, and commercial decision-making. This is a hands-on role ideal for someone early in their career who is eager to build strong foundations in data management and grow within Amgen’s Customer Data & Analytics (CD&A) organization.
Job Responsibility:
Perform day-to-day data stewardship activities across master data domains (e.g., HCP/HCO, Affiliations, Payer/Plan, Product, Patient, Consent)
Execute data creation, updates, merges, de-duplication and remediation activities in line with defined MDM business rules and SOPs
Run data quality checks and validations, investigate anomalies, and escalate issues to senior team members where needed
Support triaging and resolution of data issues received from stakeholders, downstream systems, and support channels
Help maintain accurate and up-to-date documentation for processes, SOPs, data dictionaries, and exception handling guidelines
Contribute to data quality monitoring, including preparation of quality metrics, dashboards, and reports
Support implementation of governance decisions by applying updated rules to day-to-day data operations
Work with Technology/IT partners to raise and track incidents, enhancements, and defects in MDM tools and related platforms
Participate in UAT / testing for new MDM features, data quality rules, and platform enhancements
document results and issues
Collaborate with peers in Data Platforms, Patient Data, Acquisition & Governance, and stakeholder teams (e.g., Incentive Compensation, Field Reporting, Analytics) to understand data needs and dependencies
Identify recurring issues or process gaps and propose ideas to improve data quality, efficiency, and automation
Support senior team members in Proof of Concept (POC) activities on new tools/technologies (e.g., Gen AI, automated matching/de-duplication)by preparing test data, executing test cases, and analyzing outputs
Stay current on MDM and commercial data best practices and apply learnings under guidance from senior team members
Requirements:
Bachelor’s degree in Engineering, Computer Science, Information Systems, Mathematics, Statistics, Life Sciences, or a related discipline
2-5 years of experience in data management, data operations, MDM, or related areas (internships and project experience can be considered)
Experience working with datasets, performing data analysis or data quality checks in a professional or academic setting
Comfortable working in global teams and across time zones and cultures
Strong English oral and written communication skills
Basic understanding of Master Data Management concepts, data models, and data quality principles
Hands-on experience with SQL, Excel or similar tools for data exploration, validation, and reporting
Exposure to any MDM / data platforms / databases (e.g., Reltio, Informatica, AWS, Redshift, Databricks, or similar) – coursework, projects, or work experience
Ability to learn quickly and understand end-to-end commercial data flows, upstream/downstream dependencies, and business rules
Strong attention to detail with a focus on accuracy, consistency, and adherence to standards and SOPs
Ability to work in an Agile / iterative environment, collaborating with cross-functional teams
Nice to have:
Experience in life sciences / healthcare / commercial data (e.g., IQVIA datasets such as DDD, XPO, LAAD
CRM data
patient/specialty pharmacy data) is a plus
Familiarity with compliance and data privacy requirements in handling customer or patient data
Exposure to cloud platforms (e.g., AWS) and modern data tools
Understanding or exposure to Scaled Agile Framework (SAFe) or similar methodologies