Technical Product Owner – Toxicology Systems

Job Function

Technology Product & Platform Management

Job Sub Function

Technical Product Management

Job Category

Scientific/Technology

All Job Posting Locations

Beerse, Antwerp, Belgium

Job Description

Johnson & Johnson Innovative Medicine is recruiting for a Technical Product Owner - Toxicology Systems, located in Spring House, PA (US), La Jolla, CA (US) or Beerse, Belgium. Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s): United States (Spring House or La Jolla) - Requisition Number: R-094926 Belgium (Beerse) - Requisition Number: Evergreen Requisition: R-096026 The Technology Product Owner for Toxicology will own the technical delivery and support of toxicology products directly supporting toxicology and compound promiscuity science. This business technology role combines deep domain and technical expertise with program-level coordination: you will define technical strategy, own roadmaps and delivery for platforms and models used by toxicology scientists, and act as the primary technical partner and escalation point for scientific stakeholders.

Key Responsibilities

• Lead the technology strategy, roadmap, prioritization, and delivery for digital products supporting toxicology workflows, aligning scientific needs, enterprise technology standards, and available delivery capacity.
• Translate scientific needs into technical requirements, success criteria, and measurable deliverables; ensure clear acceptance criteria and productization pathways.
• Provide hands-on technical leadership when it adds the most value, including architecture definition, rapid prototyping, design reviews, and evaluation of pipelines and models; coordinate delivery across engineering, data, quality, and scientific partner teams.
• Ensure robust data ingestion, normalization, annotation, and QC processes; drive integrations with LIMS, ELN, assay instruments, and third-party data providers.
• Define and promote fit-for-purpose practices for data provenance, metadata standards, FAIR principles, and auditability to support scientific reproducibility and applicable compliance requirements.
• Act as primary technical liaison for toxicology scientists: capture requirements, demo solutions, gather feedback, and drive adoption.
• Lead technical evaluations of vendors and third-party solutions, provide due diligence and risk assessments, and coordinate integrations with procurement, legal, cybersecurity, quality, and engineering partners.
• Communicate product status, value, trade-offs, dependencies, and technical risks to leadership and cross-functional stakeholders; facilitate decisions and elevate issues when appropriate.

Qualifications Required

• Bachelor's degree in Computer Science, Bioinformatics, Computational Chemistry, Toxicology, or related field required; Master's or PhD preferred.
• 5+ years of experience supporting scientific research platforms.
• Demonstrated depth in designing, delivering, and sustaining data platforms, analytics products, or machine learning solutions in life sciences, drug discovery, or another complex scientific environment.
• Demonstrated track record of leading technical programs or major projects end-to-end in a complex organization.
• Scientific literacy in toxicology and compound promiscuity concepts: assay types, ADME endpoints and off-target profiling.
• Maintain sufficient software and data engineering depth to guide solution design, evaluate implementation quality, and contribute directly when needed, including experience with Python or R, SQL, REST APIs, containerization, CI/CD practices, and cloud environments.
• Systems and architecture skills: ability to design scalable, maintainable platforms that meet scientists' needs and regulatory constraints.
• Product and delivery leadership: define product outcomes, shape roadmaps, prioritize investments, establish success measures, manage dependencies and risks, and align cross-functional partners around delivery decisions.
• Operational leadership: establish support models, service expectations, lifecycle plans, and escalation paths for production solutions; use reliability, adoption, quality, and value measures to guide continuous improvement.
• Executive-ready communication and influence: explain technical choices, business value, delivery trade-offs, and risk to scientific, technology, and leadership audiences; build alignment and drive decisions without direct authority.
• Strong problem-solving mindset and bias for pragmatic, evidence-driven solutions.

Preferred