FSP Associate Manager, Safety Data and Systems - Pharmacovigilance

Thermo Fisher Scientific • Morrisville, NC

5d • Onsite

About The Position

This role focuses on applying AI/ML and NLP methods to safety data within GxP-validated, explainable, and regulator-defensible frameworks. The Associate Manager will lead deliverables for GPS Safety Data Management and Safety System Maintenance activities, providing high-quality data outputs for Safety Signal Management, Risk Management, and Safety Evidence generation. Collaboration with client functions and vendors is key for seamless GPS Safety Data and Systems operations.

Requirements

• At least Bachelor's degree (or country equivalent) in computer science, data science, computational linguistics, applied statistics/biostatistics, life sciences / Information technology or other relevant field required.
• Proficiency in Python for ML development, including scikit-learn, pandas, NumPy; experience with at least one deep learning framework (PyTorch or TensorFlow).
• Natural language processing for extraction of adverse events, drugs, and outcomes from unstructured text - case narratives, medical literature, call transcripts, and spontaneous reports.
• Named Entity Recognition (NER), relation extraction, and text classification.
• Experience with transformer-based / large language models (BERT-family, clinical/biomedical models such as BioBERT or PubMedBERT, and modern LLMs) for narrative generation, summarization, and information extraction.
• MedDRA and WHODrug auto-coding using ML/NLP; prompt engineering and retrieval-augmented generation (RAG) a plus.
• Supervised and unsupervised methods for classification, clustering, and anomaly detection.
• Feature engineering and model evaluation (precision/recall trade-offs, ROC/AUC, calibration) with an understanding of why recall and sensitivity are weighted heavily in a safety context.
• Model lifecycle management: versioning, monitoring, drift detection, retraining pipelines using standard MLOps tooling (e.g., MLflow, Azure ML, Databricks) in line with client DT/BIS standards.
• Model explainability / interpretability (SHAP, LIME) - essential where decisions must be defensible to health authorities.
• Understanding of GxP / GAMP 5 validation as applied to AI/ML systems, model governance, and emerging regulatory expectations (EMA reflection paper on AI, FDA guidance).
• Proficiency in Safety Database systems (e.g., Argus) and knowledge of other technical systems applicable to Safety /Pharmacovigilance (e.g., E2B gateway, safety signal detection tools and systems) is a plus.
• Proficiency in electronic systems commonly used for Safety / PV, like for data visualization and analysis, dashboards.
• Solid understanding of the quality management processes, metrics and KPIs.
• Good knowledge of relevant pharmacovigilance regulatory requirements and guidance documents (including Europe, US, Japan).
• Proficient in the Microsoft 365 stack (Excel, Word, PowerPoint, Teams, SharePoint, OneDrive) and in modern collaboration and documentation tooling.
• Advanced Excel required; working proficiency in SQL required for querying safety and operational datasets.
• Ability to communicate effectively and collaborate successfully across functions and with vendors.
• Fluent communication in written and spoken English required.
• Ability to work independently with minimal oversight and prioritize effectively.
• Ability to complete multiple complex deliverables within tight timelines.
• Ability to function effectively in a team environment.
• Python, ML/NLP frameworks, model deployment/monitoring, MLOps tooling, ideally exposure to LLMs on unstructured clinical/safety text.
• Familiarity with, or ability to rapidly acquire, GVP/21 CFR 314 concepts preferred.
• Working understanding of safety database data models (Argus/ArisG) and E2B(R3) structure.
• Relevant experience in IT / Safety / Clinical Research / Pharmacovigilance overall with at least 3 years of proven experience with safety database systems (e.g. ARGUS or ArisG) including workflow management.
• Equivalent and adequate combination of education and experience or proven practical expertise in all of the required skills.

Nice To Haves

• Understanding of GxP / GAMP 5 validation as applied to AI/ML systems, model governance, and emerging regulatory expectations (EMA reflection paper on AI, FDA guidance) — rare and worth flagging as preferred.

Responsibilities

• Design, develop, and validate AI/ML and NLP components that support safety operations, including MedDRA/WHODrug auto-coding, case triage, duplicate detection, and narrative summarization, with clear human-in-the-loop checkpoints.
• Contribute to model lifecycle management for safety-relevant AI/ML: versioning, monitoring, drift detection, retraining, and documentation aligned with GxP / GAMP 5 and internal model governance.
• Support the qualification of AI/ML solutions against evolving regulatory expectations (EMA reflection paper on AI, FDA AI/ML guidance, EU AI Act obligations for high-risk systems) in partnership with Quality, DT/BIS, and GPS Signal Management.
• Serve as the key technical resource for the configuration, maintenance, and administration of the Oracle Argus Safety system.
• Support day-to-day operation and troubleshooting of safety systems.
• Assist in system validation, testing, and deployment of safety systems updates.
• Generate, validate, and customize safety reports and analytics.
• Collaborate closely with the pharmacovigilance, clinical, and regulatory teams to ensure safety data management aligns with global regulatory standards (FDA, EMA, PMDA, ICH).
• Participate in change management processes to enhance safety system integrations.
• Contribute to audit readiness activities, including system inspections, validation reports, and compliance documentation.
• Collaborate with internal systems team, BIS/DT, and Safety vendor on issues related to Safety data.
• Perform the generation and quality control of aggregate reports and line listings.
• Initiate and contribute to the development of procedural documents including but not limited to Safety Management Plans, SOPs, work instructions, job aides, forms, or templates.
• Collaborate and co-create with applicable client functions (e.g., Medical Information, Data Management, Business Information Systems, Quantitative Science) in regards to pharmacovigilance technical aspects, setup, and operation.
• Keep up-to-date on applicable regulatory and PV tech guidelines and share within GPS and client as applicable.
• Participate in training related to safety data management.
• Proactively review processes and tools and provide suggestions for improvement and better efficiencies.
• Complete additional tasks and projects as assigned by line manager or delegate.

Benefits

• Thermo Fisher Scientific values the health and wellbeing of our employees. We support and encourage individuals to create a healthy and balanced environment where they can thrive.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level