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Principal Data Scientist – AI/ML, Optimization
Johnson & Johnson. Conceive, develop, and implement ML, multi-objective optimization, and GenAI solutions supporting clinical trial operations .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in developing and implementing Machine Learning and multi-objective optimization solutions for clinical trial operations, with a strong focus on predictive modeling, natural language processing, and GenAI applications. Proficient in utilizing MLOps practices and tools to enhance operational efficiency and decision-making in healthcare settings.
Highest-signal resume keywords
Ph.D. In Quantitative DisciplineMachine Learning Predictive ModelingMulti-Objective OptimizationNatural Language ProcessingMLOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Predictive ModelingMulti-Objective OptimizationStochastic SimulationsPython ProgrammingSQL ProficiencyGenAI ApplicationsEvolutionary AlgorithmsReinforcement LearningMixed-Integer Linear ProgrammingClinical Trial Protocols
Soft Skills
CoachingCommunication
Tools & Technologies
MLflowKedroGitJenkinsGitLabDSPyLangChainScikit-learnXGBoostOptuna
Industry Keywords
HealthcareMedTechPharmaceuticalsClinical Operational DataReal World DataElectronic Health RecordsClaims DataFinancial DataClinical Trial Management SystemsRegistry Data
Tech Stack
Tools & technologiesJenkinsPythonScikit-LearnSQL
About the role
Key responsibilities & impact- Conceive, develop, and implement ML, multi-objective optimization, and GenAI solutions supporting clinical trial operations
- Develop predictive ML models to forecast operational time-series outcomes and KPIs
- Formulate and solve optimization problems quantifying tradeoffs among cost, timelines, patient burden, quality, and operational efficiency
- Integrate predictive modeling with optimization to evaluate operational scenarios, assess outcomes, and recommend optimal strategies
- Build explainable decision-support systems enabling proactive planning, early risk identification, and informed business decision-making
- Adapt large language models for information extraction, comparative clinical trial protocol analytics, trial similarity assessment, clinical trial data harmonization and standardization, schedule of activity optimization, and eligibility criteria evaluation
- Conduct stochastic enrollment simulations forecasting enrollment, study completion, and patient journey outcomes
- Clearly articulate technical methods and results to diverse audiences and partners
- Coach and train junior colleagues
Requirements
What you’ll need- A Ph.D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar)
- 5+ years of industry experience delivering on data science projects using ML predictive modeling, multi-objective optimization, natural language processing, and GenAI
- Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting
- Experience building multi-objective optimization engines using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming
- Experience with GenAI and clinical LLMs for document parsing and clinical concept disambiguation and harmonization
- Proficient in MLOps practices and tools (MLflow, Kedro)
- Git usage and CI/CD stacks (Jenkins, GitLab) DevOps tools
- Proficiency with programming languages Python and SQL
- Experience with Python LLM tools (e.g., DSPy, LangChain), optimization tools (e.g., pymoo), and ML tools (e.g., Scikit-learn, XGBoost, Optuna, PyMc)
- Demonstrated experience and familiarity with clinical operational data, real world data, electronic health records and claims, and financial data
- Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries
- Hands-on experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC and/or EHR to build ML models for estimating operational outcomes or RWE outcomes
Benefits
Comp & perks- annual bonus with set target (% of pay) depending on pay grade / location
- vacation days
- parental leave for a minimum of 12 weeks
- bereavement leave
- caregiver leave
- volunteer leave
- well-being reimbursement
- programs for financial, physical and mental health
- service anniversary and recognition awards
- insurance plans for employees and, in some locations, eligible dependents