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Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Data ScienceJob Category:
Scientific/TechnologyAll Job Posting Locations:
Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of AmericaJob Description:
J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Scientist. The ideal candidate will Lead analytics, ML, optimization, and GenAI that rely primarily on real‑world data to inform clinical trial design, feasibility, and execution facilitation, translate insights from RWD sources (e.g., EHR, claims, registries, digital health) into clear recommendations that shape protocol decisions and operational plans.
J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine
Key responsibilities:
Use RWD to quantify disease prevalence, care pathways, and the impact of inclusion/exclusion criteria; produce feasibility scoring across geographies, sites, and subpopulations.
Assess RWD‑feasible endpoints and proxies; evaluate availability, completeness, quality, and signal‑to‑noise to guide protocol design choices.
Construct RWD‑based cohorts and external/synthetic controls to benchmark protocol decisions and stress‑test sample‑size/timeline assumptions.
Develop ML and multi‑objective optimization solutions primarily powered by RWD to surface trade‑offs (speed, quality, cost, diversity) and recommend design and operational scenarios informed by real‑world care patterns.
Build RWD‑calibrated stochastic simulations of patient journeys to forecast timeline sensitivities and completion risk; provide RWD features, calibration sets, and feasibility constraints to the partner team’s enrollment/screen‑failure/retention models.
Adapt LLMs/GenAI for structured extraction from RWD artifacts (structured and unstructured EHR, notes, radiology/pathology reports, claims, registries); harmonize concepts to standard vocabularies to support eligibility criteria evaluation and schedule‑of‑activities insights grounded in real‑world practice.
Clearly communicate RWD‑based assumptions, methods, and results to clinical, operational, and leadership stakeholders; coach and mentor colleagues on RWD methodologies, pipelines, and best practices.
Required qualifications:
A Ph.D. degree in quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar),
5+ years delivering ML/NLP/GenAI and multi objective optimization solutions with primary reliance on RWD (EHR, claims, registries, digital health), including collaboration with operations analytics teams.
Hands on experience with multimodal RWD (structured + unstructured) predictive modeling and stochastic simulations for feasibility and time series scenario forecasting.
Demonstrated ability to construct, validate, and deploy models from RWD to inform trial feasibility, endpoint selection, eligibility criteria effects, and external control design.
Experience building optimization engines (e.g., evolutionary algorithms, reinforcement learning, mixed integer linear programming) using RWD derived signals to navigate complex tradeoffs.
Proficiency in MLOps (e.g., MLflow, Kedro), Git, and CI/CD; strong programming skills in Python and SQL; familiarity with DSPy/LangChain, pymoo, scikit learn, XGBoost, Optuna, PyMC.
Familiarity with healthcare privacy/compliance, de identification practices, and RWD data quality management; ability to integrate outputs from operational systems/models when needed while keeping the analytical core RWD driven.
Preferred qualifications:
Demonstrated expertise applying RWD methods to inform trial design: target trial emulation, propensity weighting/matching, and survival/time‑to‑event analyses for endpoint feasibility and external/synthetic controls.
Proven collaboration with operations analytics teams by supplying RWD‑derived cohorts, features, and feasibility evidence that improved enrollment forecasting, site selection, and diversity goals.
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 ([email protected]) or contact AskGS to be directed to your accommodation resource.
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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 AnalysisThe anticipated base pay range for this position is :
$117,000.00 - $201,250.00Additional 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)).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
Skills Required
- Ph.D. in a quantitative discipline (computer science, ECE, biostatistics, health economics, biomedical informatics, applied mathematics, or similar)
- 5+ years delivering ML/NLP/GenAI and multi-objective optimization solutions primarily using real-world data (EHR, claims, registries, digital health)
- Hands-on experience with multimodal RWD predictive modeling and stochastic simulations for feasibility and time-series forecasting
- Ability to construct, validate, and deploy RWD-derived models for trial feasibility, endpoint selection, eligibility criteria effects, and external/synthetic control design
- Experience building optimization engines (evolutionary algorithms, reinforcement learning, mixed integer linear programming) using RWD-derived signals
- Proficiency in MLOps (e.g., MLflow, Kedro), Git, CI/CD; strong programming skills in Python and SQL
- Familiarity with DSPy/LangChain, pymoo, scikit-learn, XGBoost, Optuna, PyMC
- Familiarity with healthcare privacy/compliance, de-identification practices, and RWD data quality management
- Experience collaborating with operations analytics teams to integrate RWD outputs into operational models
- Expertise in target trial emulation, propensity weighting/matching, and survival/time-to-event analyses for external/synthetic controls
Johnson & Johnson Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Johnson & Johnson and has not been reviewed or approved by Johnson & Johnson.
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Healthcare Strength — Healthcare coverage is characterized as comprehensive across medical, dental, and vision, with added supports like onsite clinics, fitness centers, and Employee Assistance resources. Mental-health services and wellbeing reimbursements are also described as meaningful components of the overall package.
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Retirement Support — Retirement offerings are portrayed as a major differentiator, combining a 401(k) with employer matching and an employer-funded pension plan. Stock options and other long-term financial supports are also positioned as part of the broader rewards mix.
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Parental & Family Support — Family-related benefits are presented as notably strong, including paid parental leave for all new parents and additional leave types for caregiving and bereavement. Financial assistance for adoption, fertility treatment, and surrogacy is highlighted as a significant support.
Johnson & Johnson Insights
What We Do
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