Job Description

Job Summary

We are seeking three highly specialized Regulatory Data Translators to act as the essential bridge between Regulatory Strategy and our advanced Data and AI teams. These roles are critical for enabling the organization to leverage Large Language Models (LLMs) and Generative AI (GenAI) capabilities using complex, unstructured regulatory data. This position requires a unique blend of regulatory expertise and a deep passion for data, focusing specifically on supporting high-priority Therapeutic Areas (TAs): Oncology, Immunology, and Neurology. The primary focus of the role is to ensure regulatory compliance and robust AI governance while translating data needs into actionable data products.

Core Responsibilities

The Regulatory Data Translator will drive the strategic application of data capabilities within their assigned Therapeutic Area (TA) through the following responsibilities:

1. Data Translation and Stakeholder Communication:

• Serve as the translating layer between the regulatory strategy function and the internal teams building data products and capabilities.

• Connect the TA’s specific data needs directly to the personnel responsible for building the necessary data products.

• Effectively communicate the features of existing data products, the capabilities of already built AI models, and upcoming data development pipelines to key stakeholders, including Global Regulatory Leads.

• Maintain comprehensive knowledge of the sources of truth for regulatory data pertinent to the assigned TA.

2. AI Governance and Risk Management (FDA Compliance):

• Own and manage AI governance within the assigned Therapeutic Area.

• Implement risk frameworks by conducting risk stratification for all Gen AI use cases, aligning with recent FDA guidance on AI governance.

• Ensure that high-risk use cases—those affecting regulatory decisions, patient-related data, efficacy, or safety—incorporate a human-in-the-loop reviewer to maintain appropriate oversight.

3. Data Product Management and Auditability:

• Oversee the transformation of unstructured regulatory data, including submission archives, labels, and correspondence, to prepare it for LLM capabilities.

• Ensure that LLM outputs and data products support a complete audit trail back to the source documents (labels, correspondence, and health authority submissions). This involves working with vectorized text and associated metadata tags to guarantee traceability.

• Manage the handling of restricted data, such as all submissions to health authorities, ensuring strict access control and compliance standards are maintained.

Required Qualifications and Experience

The ideal candidate will be a "unicorn" profile, blending strong regulatory strategy expertise with a fundamental understanding of AI application

Regulatory Expertise (Approximately 90% of Skill Set):

• 3–5 years of experience in Regulatory Strategy is essential, balancing foundational knowledge with enthusiasm for hands-on, AI-focused work. Candidates who are too junior may lack understanding of necessary developmental questions, while those who are too senior may not be interested in the hands-on AI focus.

• Experience in the Pharma industry is strongly preferred, demonstrating a proven prioritization of compliance over speed.

• Prior experience as a North America regulatory lead for Oncology, Immunology, or Neurology would be ideal.

Data & Technology Fluency:

• Demonstrated passion for data and IT-driven topics.

• Familiarity with the application of Generative AI (GenAI) concepts and practical AI use cases.

• Must have history collaborating with IT teams and some experience with solution building, although this is not a data science role.

Education:

• Advanced degrees (such as Master's, PhD, or PharmD) are common for regulatory strategists and preferred, but demonstrated experience is prioritized over a specific degree.

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