Associate Data Quality Analyst

About McKesson Compile

Established in 1833, McKesson is a US Fortune 10 global leader in healthcare supply chain management solutions, retail pharmacy, healthcare technology, community oncology, and specialty care. We partner with life sciences companies, manufacturers, providers, pharmacies, governments, and other healthcare organizations to help provide the right medicines, medical products, and healthcare services to the right patients at the right time, safely and cost effectively.

Based in Bangalore India, McKesson Compile's data is a comprehensive, full linked system of record for the US Healthcare market, with intelligence on 2M+ healthcare professionals (HCPs) and over 800K facilities. Compile's data includes high capture medical and pharmacy claims, closed capture Medicare claims (100%), along with best-in-class provider affiliations and customer master.

At McKesson we deliver careers with purpose and potential. Our focus on better health starts with creating an inclusive environment with strong values where you can build a fulfilling career. You can count on us to provide you with resources and opportunities to grow and be your best, while contributing to our pursuit of improving lives.

Job Title: Associate Data Quality Analyst

Location: Bangalore, KA Department: Data Research - Product

Role Overview

As an Associate Data Quality Analyst, you will play a critical role in curating and validating healthcare data that powers machine learning models and enhances product intelligence. You will be responsible for ensuring the accuracy, consistency, and completeness of data used across our platforms, with a strong focus on healthcare-related datasets.

Roles and responsibilities

• Collect, cleanse, and validate healthcare data that are not machine-readable.

• Maintain consistency and accuracy across datasets through regular validation and updates.

• Evaluate data outputs and flag inconsistencies or inaccuracies.

• Analyze datasets to identify anomalies, trends, and potential errors.

• Conduct detailed online research to gather, verify, and update data relevant to our product.

• Monitor real-time organizational changes by tracking Merger & Acquisition activities and updating relevant data accordingly.

• Contribute to building a linked dataset of the US healthcare ecosystem by mapping complex affiliation relationships among IDNs, hospitals, and providers using diverse data sources such as claims and regulatory filings.

• Build domain expertise in US healthcare systems and Affiliations data to enhance data relevance and quality.

• Identify anomalies, patterns, and correlations within large datasets to support predictive analytics and improve data-driven decision-making.

• Document key analyses and effectively communicate insights to the Product and Data Science teams.

• Working closely with Senior Associate Data Quality Analyst and team leads to understanding project scope, objectives, and timelines.

• Communicate blockers, data-related issues, and suggestions for process improvements clearly and proactively.

• Collaborate with cross-functional teams to investigate and resolve client-reported data issues.

Basic Qualifications

• Only candidates with a Bachelor's or master's degree in Biotechnology, Pharmacy, Life Sciences or Biomedical Sciences are eligible.

• 0-1 year experience and proficiency in Microsoft Excel or other data analysis tools.

• SQL proficiency is required for querying and managing structured data in this role.

• Strong analytical and technical skills with a keen eye for detail.

• Demonstrated experience in conducting research and generating actionable insights.

• Excellent written and verbal communication skills, with the ability to clearly present findings and collaborate across teams.

• Outstanding internet research capabilities and ability to synthesize information from diverse sources.

Preferred Qualification

• Familiarity with US Health Care/Pharma/Life Sciences terminology is a plus.

• High level of motivation, self-discipline, and ability to manage tasks independently.