Senior Principal Data Scientist - Cataloging & Metadata

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Titusville, New Jersey, United States of America

Job Description:

Job Description

Johnson and Johnson Innovative Medicine (J&J IM), a pharmaceutical company of Johnson & Johnson is recruiting for a Cataloging Data Scientist 

This position has a primary location of Titusville, NJ but is also open to candidates from Cambridge, Boston , Madrid, Spain 

About Innovative Medicine  

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine 

We are searching for the best talent for Senior Principal Data Scientist - Cataloging & Metadata

Purpose

We are seeking a Sr. Principal Data Scientist for Cataloging, Metadata and Governance Team to design, develop, and implement automated AI solutions that address complex enterprise business challenges. In addition to building robust AI models, you will play a key role in enhancing data quality by curating, validating, and enriching metadata from multiple sources, and conducting quality checks on all relevant data fields. You will collaborate closely with Data Management, Platform Teams, Product Owners, and Business stakeholders to support catalog automation setup, improving data catalog usability and ensuring seamless data access for analytics and decision-making. 

The Senior Principal Data Scientist - Cataloging & Metadata collaborates with cross-functional teams, including Data Management, Platform Teams, Product Owners, and Business stakeholders—to ensure metadata from multiple sources is curated, validated, and enriched, and that quality checks are rigorously performed across all relevant data fields. This role aligns with catalog automation initiatives, enhances data catalog usability, and supports seamless data access to empower analytics and informed decision-making. In addition to these core responsibilities, the Cataloging Data Scientist also designs, develops, and implements generative AI solutions that are closely integrated with cataloging processes, further enhancing the discoverability, findability, and overall usability of the data catalog, and driving continuous improvement in data management and discovery. 

You will be responsible for:

• Own solutioning, developing and implementing solutions for the data cataloging, metadata and governance team.

• Lead the curation and ongoing management of the enterprise data catalog by capturing, validating, and enriching metadata from diverse sources, ensuring that business terms, data elements, and approved definitions are documented in collaboration with Data Owners and SME’s. 

• Monitor catalog adoption and usage, continuously enhancing catalog usability and searchability so that all critical datasets, data products, and master data entities are indexed, discoverable, and accurately described. 

• Implement rigorous data quality assessments, applying validation and enrichment techniques to maintain the reliability, accuracy, and contextualization of metadata throughout the data lifecycle. 

• Develop and monitor KPIs for metadata quality, completeness, and compliance across domains. 

• Works closely with cross-functional teams—including Knowledge Management, Data Products, and other groups—to integrate catalog automation and metadata capabilities into broader enterprise workflows, supporting seamless data accessibility and governance. 

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