Associate Manager, Safety Data and Systems – Pharmacovigilance

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Create, develop, and validate AI/ML and NLP components that enhance safety operations, including auto-coding, case triage, duplicate detection, and narrative summarization.

• Contribute to the lifecycle management of safety-focused AI/ML models, encompassing versioning, monitoring, drift detection, retraining, and documentation.

• Assist in the qualification of AI/ML solutions in accordance with regulatory standards in collaboration with Quality, DT/BIS, and GPS Signal Management.

• Act as the primary technical resource for the configuration, maintenance, and management of the Oracle Argus Safety system.

• Support daily operations and troubleshooting of safety systems.

• Aid in system validation, testing, and the rollout of safety system updates.

• Create, validate, and tailor safety reports and analytics.

• Collaborate with pharmacovigilance, clinical, regulatory, client, internal systems, BIS/DT, and vendor teams.

• Engage in change management to improve safety system integrations.

• Assist in audit preparedness, inspections, validation reports, and compliance documentation.

• Produce and ensure the quality of aggregate reports and line listings.

• Draft procedural documents, including Safety Management Plans, SOPs, work instructions, job aids, forms, and templates.

• Stay updated on regulatory and pharmacovigilance technology guidelines and share insights.

• Participate in safety data management training sessions.

• Review processes and tools, recommending improvements for efficiency.

• Lead deliverables related to GPS Safety Data Management and Safety System Maintenance.

• Provide high-quality data outputs for Safety Signal Management, Risk Management, and Safety Evidence generation.

• Undertake additional tasks and projects as assigned by the line manager or their delegate.

⛳️ Requirements

• A minimum of a Bachelor’s degree (or equivalent from another country) in computer science, data science, computational linguistics, applied statistics/biostatistics, life sciences, information technology, or a related field.

• At least 3 years of demonstrated experience with safety database systems such as ARGUS or ArisG, including workflow management.

• Relevant background in IT, Safety, Clinical Research, or Pharmacovigilance.

• An equivalent combination of education and experience or proven practical expertise may also be considered.

• Proficiency in Python, including familiarity with scikit-learn, pandas, and NumPy.

• Experience with at least one deep learning framework, such as PyTorch or TensorFlow.

• Background in NLP, specifically in adverse event, drug, and outcome extraction from unstructured text.

• Experience with named entity recognition, relation extraction, and text classification.

• Familiarity with transformer-based or large language models, including BERT-family, BioBERT, PubMedBERT, or contemporary LLMs.

• Experience in supervised and unsupervised classification, clustering, and anomaly detection.

• Experience in feature engineering and model evaluation, including precision/recall, ROC/AUC, and calibration.

• Experience with model lifecycle management, versioning, monitoring, drift detection, and retraining pipelines using MLOps tools such as MLflow, Azure ML, or Databricks.

• Knowledge of model explainability/interpretability techniques such as SHAP or LIME.

• Understanding of GxP/GAMP 5 validation, AI/ML model governance, and emerging regulatory expectations.

• Working knowledge of safety database data models, including Argus/ArisG, and E2B(R3) structure.

• Advanced proficiency in Excel and working knowledge of SQL is required.

• Proficiency in Microsoft 365 and collaboration/documentation tools.

• Strong understanding of quality management processes, metrics, and KPIs.

• Good grasp of pharmacovigilance regulatory requirements and guidance documents applicable in Europe, the US, and Japan.

• Fluent written and spoken English is essential.

• Capability to work independently, prioritize effectively, manage multiple complex deliverables within tight deadlines, and collaborate effectively within a team environment.

🏝️ Benefits

• Fully remote work arrangement.

• Standard Monday–Friday work schedule.

• A healthy and balanced working environment supported by Thermo Fisher Scientific.