Data specialist /curator for Large Language Models-derived toxicological (meta)data

Flexsis is part of the Interiman Group, one of the leading providers of personnel services in Switzerland. Thanks to our solid expertise and the competences within the Interiman Group, we offer tailor-made solutions in personnel consulting.

For our client F. Hoffmann - La Roche in Basel, we are looking for a motivated and reliable (m/f/d)

Data specialist /curator for Large Language Models-derived toxicological (meta)data 80-100%

• Data Validation:
• Review toxicological data output generated by LLMs and validate it against original resources (e.g., research articles, regulatory documents, toxicology databases).
• Identify and document discrepancies, errors, or ambiguities in AI-derived data.
• Build up pipeline/dataset (choose one if needed) for toxicological evaluation tasks
• Quality Assurance:
• Ensure consistency, completeness, and scientific accuracy of curated toxicological datasets.
• Adhere to established quality control protocols and contribute to improving workflows as needed.
• Toxicology Expertise:
• Apply toxicological knowledge to evaluate data related to preclinical and clinical toxicities, mechanisms of toxicity, safety biomarkers, and risk assessments.
• Assess relevance and applicability of curated data to specific drug development scenarios.
• Collaboration:
• Work closely with computational toxicologists, data scientists, and cross-functional teams to align on curation standards and requirements.
• Provide feedback to enhance LLM performance based on identified gaps or inaccuracies in the extracted data.
• Documentation and Reporting:
• Maintain detailed records of validation processes and outcomes.
• Prepare periodic reports summarizing curation progress, data quality metrics, and key findings.

• Preferred Master's in Biology, Pharmacology, Toxicology, Drug Development, Biotechnology or a related field. 
• Experience with data curation, annotation, or systematic review methodologies is a plus. 
• Basic understanding of machine learning, LLMs, or natural language processing (NLP) tools is desirable but not required.
• English fluent (mind. C1 Level) 
• Strong attention to detail and commitment to data accuracy. 
• Excellent critical thinking and problem-solving skills, particularly in evaluating scientific information.
• Ability to synthesize complex toxicological data and present clear, actionable conclusions.
• Effective written and verbal communication skills for reporting and collaboration.