Principal Data Scientist - DDSAI - Agentic Lab Automation

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 jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world.  We provide an inclusive work environment where each person is considered as an individual.  At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Spring House, Pennsylvania, United States of America

Job Description:

About the Role 

Johnson & Johnson Innovative Medicine is seeking a Principal Scientist, Agentic Lab Automation to help build our drug discovery labs of the future in Spring House, PA. This is an opportunity to be one of the early experts shaping a next-generation DMTA discovery engine that integrates robotic lab execution, real-time data pipelines, intelligent orchestration, and agentic AI workflows to accelerate how we discover and develop new medicines. 

In this role, you will work at the intersection of scientific experimentation, lab automation, AI systems, and digital infrastructure, helping transform today's human-in-the-loop processes into more scalable, connected, and intelligent discovery workflows. You will partner across Therapeutics Discovery, Data Science, and IT to enable laboratory systems that generate high-value data, improve scientific learning with every cycle, and unlock new speed, quality, and strategic advantage for our pipeline. 

This role is ideal for a technically deep and creatively ambitious scientist/engineer who wants to help build our future discovery engine, not just automate steps, but architect how scientific and physical AI come together to steer design and execution in the lab. 

Why This Role Is Unique 

This is a rare chance to build a closed-loop AI driven discovery engine in Spring House, PA, one of JnJ’s key Discovery hubs. The role will contribute to a broader shift toward automation engineering and AI-enablement that can improve the quality and speed of our molecules to strengthen long-term competitive advantage. 

Key Responsibilities 

1) Lab Orchestration & Integration 

• Translate scientific priorities into automation and AI roadmaps, connecting tactical platform work to long-term discovery goals. 
• Design, configure, integrate, and continuously improve the AI execution of robotic lab systems that support high-throughput data generation. 

• Build or oversee the development of real-time pipelines connecting automation software, data stores, models, and compute environments. 

• Partner with IT and platform teams to implement resilient APIs, observability, versioning, and workflow orchestration for end-to-end discovery processes. 

2) AI-Driven Scientific Learning 

• Design and implement laboratory workflows and experiments optimized for AI-driven learning, not just throughput or task automation. 

• Collaborate with AI/ML scientists to enable closed-loop feedback between each step in the DMTA process, ensuring experimental outputs improve downstream models and decision-making. 

• Identify opportunities to apply agentic AI and intelligent automation to compress cycle time, reduce manual intervention, and improve reproducibility. 

3) Data, Semantics & AI Readiness 

• Ensure data generated through automated workflows is high-quality, traceable, interoperable, and AI-ready, with strong metadata, provenance, lineage, and governance practices. 

• Collaborate with data engineers, ontology/knowledge engineers, and platform teams to standardize assay outputs, semantically enrich datasets, and support discoverability across modalities. 

• Contribute to architectures that support vectorized, semantically searchable, and reusable scientific data assets across discovery workflows. 

4) Cross-Functional Leadership & External Engagement 

• Serve as a senior technical partner across Discovery, Data Science, and IT to align scientific goals with Agentic orchestration.
• Help quickly shape standards, priorities, and new ways of working. 

• Evaluate emerging vendors, tools, and external capabilities relevant to robotics, AI orchestration, and AI-enabled lab execution. 

Qualifications 

Required 

• Ph.D. (or equivalent advanced degree) in Engineering, Automation, Robotics, Computer Science, Biomedical Engineering, Chemical Engineering, Systems Engineering, Computational Biology, or a related field. 

• Significant industry experience building, integrating, or scaling laboratory automation, AI-enabled experimentation platforms, or autonomous workflow systems in pharma, biotech, advanced R&D, or adjacent technical environments. 

• Demonstrated expertise in one or more of the following: robotic lab systems, scientific workflow orchestration, laboratory informatics, experimental platform integration, automation software, or cyber-physical systems for R&D. 

• Experience designing or supporting real-time or near-real-time data pipelines and integrating heterogeneous scientific data and instrument outputs. 

• Ability to work directly with experimental scientists and translate scientific objectives into practical, scalable technical solutions. 

• Strong communication, problem-solving, and stakeholder management skills, with comfort operating in ambiguity and shaping new capabilities at scale. 

Preferred 

• Experience applying agentic AI, AI/ML, optimization, or intelligent decision systems to scientific or laboratory workflows. 

• Familiarity with MLOps/DevOps, workflow engines, and production-grade monitoring/observability. 

• Understanding of FAIR data, ontologies, semantic models, lineage/provenance, or AI-ready scientific data standards. 

• Experience in drug discovery domains such as small molecules, biologics, peptide discovery, high-throughput experimentation, imaging, or human-relevant model systems. 

What Success Looks Like 

• Automated and agentic lab workflows are operating in ways that are scientifically meaningful, scalable, and tightly connected to data and AI systems. 

• Laboratory data is captured with the quality, semantics, and traceability needed to support closed-loop scientific learning and downstream model improvement. 

• Discovery teams can move faster from hypothesis to experiment to insight through better orchestration, higher-quality data, and reduced fragmentation across process steps. 

Why This Role Is Unique

This is a rare opportunity to grow in one of the world’s most ambitious and fastest-growing Pharma R&D Data Science organizations, shaping how TD data powers next‑generation therapies in the largest biomedical company on the planet. Your work will directly accelerate Johnson & Johnson’s scientific discovery, fuel AI innovation, and impact patients globally.

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 & 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, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.

#JRDDS

#JNJDataScience

JNJIMRND-DS

Required Skills:

 

 

Preferred Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

 

 

The anticipated base pay range for this position is :

$117,000.00 - $201,250.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).



This position is eligible to participate in the Company’s long-term incentive program.



Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:

Vacation –120 hours per calendar year

Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year

Holiday pay, including Floating Holidays –13 days per calendar year

Work, Personal and Family Time - up to 40 hours per calendar year

Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child

Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year

Caregiver Leave – 80 hours in a 52-week rolling period10 days

Volunteer Leave – 32 hours per calendar year

Military Spouse Time-Off – 80 hours per calendar year

For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits