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JOB DESCRIPTION:

The Principal Scientist, Safety Data Science leads the development and deployment of medical safety data models into production.
This role plays a pivotal part in advancing AI/Machine Learning (ML) capabilities within the Global Medical Safety organization by developing ground breaking solutions and leading projects that deliver measurable business impact.
Collaborates closely with IT teams, business partners, and scientific authorities to ensure flawless model deployment and alignment with functional priorities.

Key Responsibilities

• Optimally deploy AI/ML models into scalable, production-grade environments while ensuring their reliability, adaptability, and business impact
• Lead end-to-end projects, including requirement gathering, solution design, implementation, and handoff
• Work closely with business collaborators to identify needs, define success metrics, and deliver impactful solutions
• Research, develop, and validate analytical models using leading AI/ML techniques, including supervised and unsupervised learning, deep learning, GenAI and natural language processing (NLP)
• Evaluate and integrate new data sources, emerging tools, and sophisticated analytics methodologies to transform the organization’s capabilities
• Design interactive dashboards and data applications to present insights clearly to non-technical partners
• Stay at the forefront of AI/ML advancements and promote innovative solutions to drive the organization forward
• Continuously refine processes and workflows to boost efficiency, effectiveness, and reproducibility of ML solutions

Qualifications

• Master’s or Doctorate degree in Data Science, Information Systems, Computer Science, Statistics, Mathematics, Bioinformatics or a related field is required
• Minimum of 5 years of industry experience in Data Science, with demonstrated deployment expertise
• Demonstrable experience in leading projects, running multi-functional teams, and collaborating effectively with business partners
• Demonstrated ability to build end-to-end data science solutions, including data ingestion, pipeline development, model training, deployment, and performance monitoring
• Experience in independently leading projects and project teams
• Healthcare or pharmaceutical experience is preferred

Skills:

• Proficiency in Python and SQL for data manipulation, analysis, and model development
• Deep experience with machine learning models and techniques (supervised, unsupervised, deep learning, LLMs, etc.)
• Hands-on expertise in deploying models using MLOps tools, pipelines and standard processes
• Experience in cloud environments, specifically GCP services such as BigQuery, AI Platform, and Dataflow, is helpful
• Practical understanding of cloud-based CI/CD pipelines for software and ML model deployment
• Outstanding problem-solving abilities with attention to detail and rigor in model validation and evaluation
• Good interpersonal skills to effectively bridge the gap between technical and non-technical partners
• Ability to work in a fast-paced, collaborative environment, managing multiple priorities
• Demonstrated capacity for innovation, creative thinking, and continual process improvement

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or contact AskGS to be directed to your accommodation resource.

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• Optimally deploy AI/ML models into scalable, production-grade environments while ensuring their reliability, adaptability, and business impact
• Lead end-to-end projects, including requirement gathering, solution design, implementation, and handoff
• Work closely with business collaborators to identify needs, define success metrics, and deliver impactful solutions
• Research, develop, and validate analytical models using leading AI/ML techniques, including supervised and unsupervised learning, deep learning, GenAI and natural language processing (NLP)
• Evaluate and integrate new data sources, emerging tools, and sophisticated analytics methodologies to transform the organization’s capabilities
• Design interactive dashboards and data applications to present insights clearly to non-technical partners
• Stay at the forefront of AI/ML advancements and promote innovative solutions to drive the organization forward
• Continuously refine processes and workflows to boost efficiency, effectiveness, and reproducibility of ML solution