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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Product Owner - Toxicology Systems - **Company:** Johnson & Johnson - **Location:** Spring House, PA, United States - **Experience:** Expert - **Salary:** $94,000.0 - $151,800.0 - **Contract:** Permanent contract - **Skills:** Bioinformatics, Continuous Integration, Information Engineering, R (Programming Language), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, Metadata Standards, Rapid Prototyping Process, Tensorflow, SQL Databases, Cloud Platform System, Data Ingestion, Pytorch, Containerization, Scikit Learn, Information Technology, Data Management, Machine Learning Operations, Restful APIs - **Published:** August 28, 2026 - **Apply:** https://www.salesheads.com/job.asp?id=3367875375&tx=FJ10602LFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role 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: * Advanced degree (MS/PhD) in toxicology, cheminformatics, computational chemistry, or related discipline. * Hands-on experience with cheminformatics tooling (e.g., RDKit), molecular representations, fingerprints, SMARTS/substructure filtering, and selectivity/promiscuity scoring approaches. * Experience with ML libraries and frameworks (scikit-learn, TensorFlow, PyTorch) and MLOps tools (model registries, monitoring). * Prior experience in regulated or GLP-relevant environments, or with quality frameworks that apply to scientific data and software. * Experience performing technical vendor evaluations and managing third-party scientific data/software integrations. ## Description 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., * 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 escalate issues when appropriate. ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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