Principal Scientist, Data Science
About The Position
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
Requirements
- 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.
Nice To Haves
- 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.
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.
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
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Ph.D. or professional degree
