Senior Scientist, Data Science, GenAI - R&D DDSAI - Therapeutics Development & Supply (TDS)

Description

The company makes medicines and medical technology. This role sits in the R&D Data Science group within Therapeutics Development & Supply (TDS).

As a senior scientist, you do hands-on individual contributor work to design, build, evaluate and deploy AI and generative AI systems that support scientific, regulatory and technical work in TDS.

You will partner with product development, manufacturing, clinical supply chain, quality, and digital and data science teams to build LLM applications, agentic workflows and AI automation. Main use cases include scientific and regulatory document writing, evidence-based answers, knowledge retrieval and synthesis, technical decision support and workflow automation.

You work with senior technical colleagues in DDSAI and deliver defined components and workflows within agreed priorities and milestones, using established architectures, reusable parts, evaluation standards and responsible AI practice.

The ideal candidate pairs practical AI development skills with knowledge of pharmaceutical CMC development and brings complex design decisions, risks and delivery problems to senior colleagues for technical input.

Responsibilities

• Develop, test and help deploy AI solutions for documentation, knowledge retrieval, evidence synthesis and decision support across TDS, with guidance on design and implementation.
• Build and test defined parts of agentic workflows that coordinate models, tools, data and human review across multi-step scientific and supply chain processes.
• Implement and adapt reusable AI capabilities using DDSAI AI/ML architectures and platform standards.
• Turn defined needs from scientific, regulatory and operational stakeholders into requirements and implementations for regulated environments, working alongside senior colleagues.
• Apply the team's evaluation frameworks for LLM systems, covering rubrics, traceability, robustness, uncertainty and usability. Add test cases and analysis to improve them.
• Follow responsible AI practice, including human-in-the-loop validation, risk assessment, content safety and governance. Flag risks and get guidance on escalation.
• Apply software engineering practice, including modular design, testing, documentation and lifecycle management, with code review and technical guidance.
• Share implementation experience and evaluation findings to shape best practice for LLM, RAG and agentic AI systems across DDSAI and TDS.
• Work with regulatory, quality, CMC, scientific and technical colleagues to clarify use-case requirements, validate outputs and support adoption.
• Use shared infrastructure, established architectures, evaluation methods and reusable components alongside DDSAI AI/ML.
• Report progress, evaluation results, system limits and risks to technical and non-technical audiences. Ask for guidance when scope, design or delivery is affected.

Requirements

• Degree in engineering, data science, life sciences, computer science or a related field.
• 1 to 3 years of hands-on experience building AI, NLP or machine learning solutions, including practical work with large language models (LLMs).
• Working knowledge of pharmaceutical product development, including chemistry, manufacturing and controls (CMC).
• Proficiency in Python, including writing, testing and documenting code.
• Strong communication skills, with the ability to explain technical topics to non-technical stakeholders.
• Preferred: an advanced degree.
• Preferred: exposure to open-source agentic frameworks such as LangGraph, DSPy or mem0.
• Preferred: familiarity with retrieval-augmented generation, embeddings, vector databases and model evaluation.
• Preferred: exposure to working in GxP regulated environments.
• Preferred: familiarity with responsible AI frameworks, content safety practices and AI governance in regulated environments.
• Preferred skills: advanced analytics, business intelligence (BI), coaching, collaboration, critical thinking, data analysis, database management, data privacy standards, data reporting, data savvy, data science, data visualization, econometric models, process improvements, technical credibility, technologically savvy and workflow analysis.

Conditions

Locations: Madrid, Spain; Spring House, Pennsylvania, United States; and Turnhout and Antwerp, Belgium.

The company treats each person as an individual and values diversity and merit.

Accommodations are available on request for applicants with disabilities.

Benefits

• Participation in the consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
• Eligibility for the long-term incentive program.
• Time-off eligibility depends on applicable policies and date of hire.
• 120 hours of vacation each calendar year.
• Sick time: 40 hours each calendar year, 48 hours for Colorado residents and 56 hours for Washington residents.
• 13 days of holiday pay each calendar year, including floating holidays.
• Up to 40 hours each calendar year for work, personal and family time.
• Parental leave: 480 hours within one year of the birth, adoption or foster care of a child.
• Bereavement leave: 240 hours for an immediate family member and 40 hours for an extended family member each calendar year.
• Caregiver leave: 80 hours over any rolling 52-week span, plus 10 days.
• Volunteer leave: 32 hours each calendar year.
• Military spouse time off: 80 hours each calendar year.