Principal Data Scientist – DDSAI GD

Johnson & Johnson•Titusville, NJ

5d•Hybrid

About The Position

Johnson & Johnson Innovative Medicine’s Data, Data Science, and AI – Global Development (DDSAI GD) is seeking a Principal Data Scientist to lead the end-to-end delivery of integrated analytical solutions for clinical-development and trial-operations business problems. The role owns solution definition, delivery, adoption, and use-case outcomes across connected stakeholder groups, using machine learning, generative AI, optimization, and real-world data. The Principal Data Scientist applies clinical, operational, cost, and real-world data—including electronic health records, claims, registries, and clinical-trial data—to generate evidence about patient populations, treatment pathways, feasibility, and operational risks. The role partners with clinical, operational, technology, and data stakeholders to shape questions, manage trade-offs, and translate analytical outputs into adopted recommendations and measurable outcomes. It also promotes sound validation, MLOps, documentation, privacy, data-quality, and responsible-AI practices; communicates findings to technical and nontechnical audiences; and mentors junior colleagues.

Requirements

Master’s degree in computer science, engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or another quantitative discipline.
At least 5 years of industry experience leading end-to-end delivery of data-science solutions using ML, predictive modeling, optimization, NLP, GenAI, or real-world-data analytics.
Demonstrated experience defining, validating, deploying, and driving adoption of analytical solutions that inform clinical-development, clinical-operations, or real-world-evidence decisions.
Hands-on experience with structured and unstructured clinical, operational, or real-world data, including multimodal modeling and time-series or simulation methods.
Proficiency in Python and SQL, modern ML, optimization, and LLM-development libraries, and reproducible MLOps practices.
Strong communication, stakeholder-management, and technical-leadership skills.

Nice To Haves

PhD in a quantitative discipline.
Experience in healthcare, pharmaceutical development, MedTech, clinical development, or clinical operations.
Experience applying real-world-data methods to clinical-trial design, including target-trial emulation, propensity methods, survival analysis, or time-to-event analysis.
Experience delivering analytical products or applications used by clinical or business teams.

Responsibilities

Own the end-to-end definition, development, validation, deployment, and adoption of integrated data-science solutions for defined business problems.
Lead predictive modeling, simulations, optimization, and GenAI applications for study feasibility, enrollment forecasting, country and site selection, protocol design, and operational planning.
Use clinical, operational, cost, and real-world data—including EHR, claims, registries, and clinical-trial data—to generate evidence on patient populations, treatment pathways, feasibility, and operational risks.
Lead real-world-data analytics that inform protocol feasibility, eligibility criteria, recruitment and retention, study design, comparative evidence, and external-control use cases.
Develop LLM-enabled workflows for information extraction, protocol comparison, data harmonization, clinical-concept interpretation, and targeted workflow automation.
Partner with clinical, operational, technology, and data stakeholders to frame questions, manage trade-offs, and translate outputs into adopted recommendations and measurable use-case outcomes.
Apply model-validation, MLOps, documentation, privacy, data-quality, and responsible-AI standards; contribute reusable code, data assets, and technical patterns.
Communicate methods, model outputs, assumptions, limitations, and decisions clearly to technical and nontechnical audiences.
Mentor junior colleagues and strengthen delivery practices across project teams.

Benefits

Company consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
Vacation: 120 hours per calendar year.
Sick time: 40 hours per calendar year, with different provisions for employees residing in Colorado or Washington.
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, or foster care of a child.
Bereavement Leave: 240 hours for an immediate family member and 40 hours for an extended family member per calendar year.
Caregiver Leave: 80 hours in a 52-week rolling period.
Volunteer Leave: 32 hours per calendar year.
Military Spouse Time-Off: 80 hours per calendar year.