Sr Principal Scientist – AI and Data Scientist for Safety Sciences

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

Discovery & Pre-Clinical/Clinical Development

Job Sub Function:

Nonclinical Safety

Job Category:

Scientific/Technology

All Job Posting Locations:

Beerse, Antwerp, Belgium

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

We are seeking a Senior Principal Scientist with confirmed expertise in artificial intelligence (AI), machine learning (ML), sophisticated analytics and data integration to join our Translational Safety Pharmacology team, within Preclinical Sciences & Translational Safety. The candidate will develop, deploy and implement new AI/ML and data science approaches to analyze and integrate diverse preclinical datasets including but not limited to safety pharmacology (in vitro/ex-vivo/in vivo, clinical), off-on target pharmacology, toxicology, biomarkers, Pharmacokinetics/Pharmacodynamics, etc.

The Senior Principal Scientist will be responsible for deploying AI/ML and data science solutions enabling the design of safer molecules earlier,  enable hypothesis generation from multi-modal data and accelerate translational insights across preclinical/clinical safety functions, as well as across drug discovery. In this position, you will be empowering scientific research as a technology authority, collaborating closely with scientists, engineers, and business collaborators to meet specific business needs within our preclinical environment by developing and leading innovative AI strategies and solutions.

Key responsibilities:

• Develop and deploy AI/ML models and data science solutions to integrate and analyze multi-parametric preclinical data (e.g., in vitro, ex vivo and in vivo pharmacology, toxicology, clinical, ADME, efficacy datasets). Champion innovation by tapping into expertise in AI, data science, and advanced modelling to propose new technical strategies that address the business challenges.
• Independently develop solutions for preclinical data aggregation, interpretation, processing, reporting and visualization of results and analytics.
• Deploy quality control measures and user adoption measures for the developed solutions.
• Build end-to-end user-friendly AI workflows and solutions that identify safety signals, mechanistic liabilities, or translational risk patterns/phenotypes across diverse data sources. Design algorithms to identify signals and patterns from sophisticated biological datasets (e.g. from radiotelemetry data to in vitro data).
• Engage in continuous collaboration with cross-functional teams, ensuring alignment of AI/ML initiatives with overall strategic project goals of the Preclinical Sciences & Translational Safety Division and driving impactful decision-making.
• Partner with IT Data Science teams to craft data architecture, ontologies, and data pipelines into a ML-ready format.
• Understand specific business needs and translate the scientific and regulatory challenges and opportunities into smarter AI solutions, and drive validation strategies for model performance. Ensure technical feasibility of proposed AI models.
• Contribute to regulatory documentation by generating mechanistic off target insights into safety hazards/risks and predictive safety assessments using AI tools that meet regulatory standards.
• Lead evaluations of novel computational methods (e.g. GenAi, multimodal findings) for applicability in preclinical safety.
• Provide expertise and mentorship on data science methodologies and AI/ML algorithms development.
• Stay at the forefront of AI/ML applications in drug discovery and safety science and represent the function at internal and external meetings.

Qualifications:

• A minimum of a Master’s degree in Computer Sciences or related field, (Computational Biology, Bioinformatics, Data Science, Artificial Intelligence, Bioengineering or related discipline) with experience in programming and data science is required
• A PhD in Computer Sciences or related field (Computational Biology, Bioinformatics, Data Science, Artificial Intelligence, Bioengineering or related discipline) is highly preferred, with experience in programming and data science (preferably in the pharmaceutical field).

Experience and Skills:

Required:

• A minimum of Master’s with 8 years proven extensive experience Data Science in industry or PhD with 5+ years of postdoctoral experience and track record in applying and managing machine learning, deep learning, or natural language processing within a pharmaceutical (preferable) or similar setting.
• Proficiency in programming (e.g., Phyton, SQL, SAS, JavaScript) and hands-on expertise in multiple coding languages, including AI/ML and statistical/analytical modelling (e.g., multivariate linear regression, cluster algorithms, logistic regression, machine learning, Neural Networks, etc.).
• Proficiency in data visualization and dashboarding frameworks (e.g., Spotfire, Tableau, R, R-Shiny, PowerBI).
• Experience in supporting scientific pharmaceutical areas, understanding of drug discovery and development workflows, particularly in the preclinical safety pharmacology and toxicology data, in vitro assays and in vivo models would be advantageous.
• Strong strategic analytical background, having the ability to translate the preclinical datasets and processes, data acquisition and management related needs into technical solutions that align with portfolio questions.
• Experience with data integration from multiple sources and working with large and disparate unstructured datasets (e.g. text mining of reports, internal report as well as available external datasets from preclinical or clinical packages).
• Excellent communication skills (English) and a strong team-oriented mindset.

Preferred:

• Experience in Biology, Preclinical Pharma industries is preferred and familiarity with biological research and medical terminology.
• Experience/Familiarity in regulatory submissions (e.g. SEND) and healthcare informatics, would be preferable.