Postdoctoral Scientist - RWE Neurology

Johnson & Johnson • Cambridge, MA

5d • Hybrid

About The Position

Johnson & Johnson Innovative Medicine is seeking an outstanding postdoctoral scientist to join the Real-World Evidence (RWE) Neurology team. This role will focus on developing real-world evidence methods to support neuroscience clinical development. The scientist will work on building practical, reusable approaches to evaluate the robustness, interpretability, and fitness-for-purpose of artificial intelligence and machine learning outputs when applied to clinical-development regulatory grade questions. The position involves working at the intersection of real-world data, historical clinical trial data, clinical outcomes, biomarkers, and selected multimodal data sources to support patient characterization, disease-trajectory modeling, endpoint assessment, and evidence generation for regulatory and clinical decision-making.

Requirements

• Ph.D. or equivalent doctoral degree in biostatistics, statistics, epidemiology, data science, biomedical informatics, computer science, computational biology, bioengineering, or a related quantitative discipline.
• Strong programming skills in R and/or Python, with experience analyzing patient-level healthcare or clinical data.
• Experience with statistical modeling, machine learning, or causal inference methods applied to biomedical, clinical, or real-world data.
• Hands-on experience with data extraction, cleaning, transformation, quality control, and reproducible analysis workflows.
• Familiarity with methods to address confounding, selection bias, missing data, measurement error, or other sources of uncertainty in observational studies.
• Strong written and verbal communication skills, with the ability to explain quantitative methods and results to multidisciplinary audiences.
• Demonstrated ability to work collaboratively in a team-based scientific environment.

Nice To Haves

• Experience with real-world data sources, such as electronic health records, insurance claims, patient registries, natural history studies, or other observational datasets.
• Familiarity with clinical trial data structures, clinical endpoints, biomarker data, or regulatory evidence-generation workflows.
• Experience with machine learning methods such as regularized regression, tree-based models, gradient boosting, survival models, representation learning, or explainable artificial intelligence methods.
• Experience conducting sensitivity analyses, model validation, robustness checks, or reproducibility assessments.

Responsibilities

• Analyze real-world data sources, observational databases, registries, and historical clinical trial data to generate insights supporting neuroscience clinical development and regulatory evidence strategies.
• Develop and apply statistical and machine learning methods to support patient subtyping, disease-progression modeling, endpoint evaluation, treatment-pattern characterization, and clinical trial design.
• Evaluate model robustness and stability under clinically meaningful changes, such as cohort definitions, biomarker thresholds, endpoint assumptions, missingness patterns, or patient-selection criteria.
• Support development of interpretable and transparent modeling workflows, including model documentation, sensitivity analyses, bias assessment, and reproducibility checks.
• Integrate structured clinical data with selected multimodal inputs, such as biomarkers, clinical narratives, digital measures, or literature-derived features, where appropriate and feasible.
• Conduct literature reviews to contextualize disease biology, clinical endpoints, real-world evidence methods, and emerging artificial intelligence approaches in neuroscience.
• Create study protocols, statistical analysis plans, analysis-ready datasets, tables, figures, and technical reports.
• Collaborate with cross-functional partners, including statistics, data science, clinical development, translational science, regulatory, epidemiology, and medical affairs teams.
• Communicate technical results clearly to both quantitative and non-technical audiences through presentations, written reports, and scientific publications.

Benefits

• Consolidated retirement plan (pension)
• Savings plan (401(k))
• Vacation – 120 hours per calendar year
• Sick time - 40 hours per calendar year (varies by state)
• 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 period
• Volunteer Leave – 32 hours per calendar year
• Military Spouse Time-Off – 80 hours per calendar year

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree