Title: Preclinical PKPD Scientist (FSP) Location: Remote Portugal Full time Remote As part of our expert team, you’ll have the opportunity to ensure operational excellence that makes a real difference in clinical pharmacology. As a Senior Sr Pharmacokineticist, you will oversee the clinical pharmacology and pharmacokinetic aspects of clinical trials from design through analysis and reporting. You will act as the lead pharmacokineticist on large or complex projects. Your responsibilities will include designing, analyzing, and interpreting pharmacokinetic, bioavailability, bioequivalence, and pharmacodynamic clinical trials through the analysis, interpretation, and review of pharmacokinetic and pharmacodynamic results. What You’ll Do: • Serves as Lead Pharmacokineticist or Pharmacokinetic Project Lead on large pharmacokinetic projects and/or development programs. • Manages pharmacokinetic project activities and timelines. • Serves as senior reviewer on pharmacokinetic projects. • Reviews clinical pharmacology deliverables and documents related to project activities. • Mentors Pharmacokineticist and Clinical Pharmacology staff on project activities. • Assists in staff training and professional development. • Participates in clinical pharmacology initiatives. • Develops and revises department SOPs and guidelines for the conduct, analysis and reporting of clinical pharmacology and pharmacokinetic trials. • Assists senior management team on departmental decision making, bid and marketing activities, recruitment, and process improvement. • Keeps updates on the regulatory guidelines with respect to pharmacokinetics and related disciplines and current trends. • Prepare/review Education and Experience Requirements: • Bachelor's degree or equivalent and relevant formal academic / vocational qualification • Previous experience that provides the knowledge, skills, and abilities to perform the job (comparable to 8+ years) or equivalent combination of education, training, and experience Years of experience refers to typical years of related experience needed to gain the required knowledge, skills, and abilities necessary to perform the essential functions of the job. Years of experience are not to be used as the only determining factor in establishing the job class or making employment selection decisions. Knowledge, Skills and Abilities: • Strong theoretical background in pharmacokinetics and knowledge of the drug development process • Knowledgeable of regulatory guidelines relevant to clinical pharmacology and pharmacokinetics areas of the drug development • Ability to apply pharmacokinetic theory and concepts using relevant software such as WinNonlin, NONMEM, SAS, S-Plus, R, or other pharmacokinetic packages • Hands-on experience in performing pharmacokinetics-pharmacodynamics modeling and simulation of clinical trial data is preferred • Good understanding of statistical methodology required in clinical pharmacology and pharmacokinetic trials • Proven management skills, as shown through management of multiple projects • Strong organizational skills across multiple complex projects, managing own and project team work loads, and the ability to adapt and adjust to changing priorities • Excellent written and verbal communications skills • Demonstrated initiative and motivation • Positive attitude, the ability to work well with others, and the ability of effectively mentor junior staff

• Lead data projects from scoping to delivery, ensuring clear direction, prioritisation, and timely execution • Work closely with business stakeholders to understand analytical needs and translate them into high-impact data products • Create robust Power BI reports, dashboards, and data models that deliver actionable insights across the business • Build, maintain, and optimise end-to-end data pipelines and systems that collect, combine, process, and deliver data • Own and drive best practice across data architecture, modelling, governance, and documentation • Act as the internal subject-matter expert for Power BI and data warehousing, providing guidance to the wider organisation • Proactively identify opportunities to improve data quality, data accessibility, and data-driven decision-making

• Design and own the mathematical and technical framework for a scalable clustering engine that groups claims based on clinical, legal, and financial attributes. • Partner with Machine Learning Engineers to translate prototypes into optimized production systems, and work with MLOps to implement automated retraining, monitoring, and model lifecycle management. • Collaborate with Data and Application Engineering teams to define APIs and data contracts that power internal tools such as attorney and physician benchmarking, as well as fraud detection systems. • Develop advanced representations of claims using both structured data (e.g., ICD codes, geographic data, indemnity and legal costs) and unstructured data (e.g., adjuster notes, medical records, legal documents). • Act as a subject matter expert within the broader engineering organization, ensuring alignment between data science initiatives, system architecture, and production reliability standards.

• Develop and optimize speech-to-text models using deep learning techniques. • Design and implement post-processing pipelines using LLMs to enhance transcription accuracy, formatting, and contextual understanding. • Build and deploy end-to-end machine learning pipelines for speech and text processing. • Fine-tune and evaluate large language models for domain-specific use cases. • Work with large-scale audio and text datasets, ensuring quality and consistency. • Collaborate with data engineers and software teams to integrate models into production systems. • Optimize models for performance, scalability, and latency. • Conduct experiments, analyze results, and continuously improve model performance. • Ensure data governance, privacy, and ethical AI practices. • Document models, methodologies, and findings for knowledge sharing.