Postdoctoral Scientist - RWE Neurology

Johnson & Johnson Innovative Medicine • Cambridge, MA

6d • $79,000 - $127,650 • Hybrid

About The Position

Johnson & Johnson Innovative Medicine is recruiting for Postdoctoral Scientist, R&D DDSAI, Real-World Evidence (RWE) Neurology. 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. The Real-World Evidence (RWE) Neurology team within Johnson & Johnson Innovative Medicine is seeking an outstanding postdoctoral scientist to help develop real-world evidence methods to support neuroscience clinical development. This role will focus on building practical, reusable approaches to evaluate whether artificial intelligence and machine learning outputs are robust, interpretable, and fit-for-purpose when applied to clinical-development regulatory grade questions. The postdoctoral scientist will work 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 (or more depending on 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