At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com
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Job Function:
Data Analytics & Computational Sciences
Job Sub Function:
Data Science
Job Category:
Scientific/Technology
All Job Posting Locations:
Irvine, California, United States of America
Job Description:
Role overview
Johnson and Johnson MedTech sector is currently recruiting for a Principal AI, Data Science & Databricks with 2–3 years of hands-on experience building and validating machine learning prediction models for MedTech. The position will be in Irvine, CA and Raritan NJ. Additional travel up to 25% may be required.
The ideal candidate will be proficient in Databricks and Python, experienced with both structured-data and unstructured-data AI (e.g., tabular models plus NLP / image models), and able to create, evaluate, and perform regression testing of prediction models under regulated product-development constraints.
Key responsibilities
- Design, build, and maintain end-to-end ML solutions on Databricks for prediction problems using structured and unstructured data.
- Implement robust data pipelines (ETL/ELT) and feature engineering using Spark / PySpark and Delta Lake.
- Develop, train, validate, and optimize supervised and unsupervised models (regression, classification, time-series, NLP, computer vision) using Python ML frameworks (Prophet, XGBoost/LightGBM, Hugging Face).
- Define and implement model evaluation strategies and metrics appropriate for commercial use
- Establish and run regression test suites for prediction models to detect performance drift across data, code, and infrastructure changes.
- Apply explainability/interpretability techniques and produce model risk and performance reports for stakeholders and auditors.
- Package, version, and register models (MLflow or equivalent) and support deployment and monitoring (CI/CD, A/B testing, model monitoring, alerting).
- Troubleshoot production issues, investigate model failures, and implement fixes with appropriate validation and traceability.
- Understand and enhance the Structured data AI and Unstructured data AI models
- Integrate the Structured and Structured data models using Agentic framework and API’s
- Working knowledge REACT, JavaScript and SQL Server
Required qualifications
- 2–3 years of professional experience in an AI/ML or data science engineering role in the MedTech industry (or closely related regulated healthcare environment).
- Strong hands-on experience with Databricks (workspace use, notebooks, jobs, clusters, Delta Lake, MLflow integration).
- Proficient in Python and common ML/data libraries (Prophet, PySpark, XGBoost/LightGBM, Hugging Face).
- Demonstrated experience building and evaluating prediction models for structured data (tabular) and unstructured data (text, images, signals).
- Experience creating and maintaining regression tests for models and pipelines; knowledge of unit and integration testing for ML components.
- Solid understanding of ML model evaluation, validation, overfitting mitigation, cross-validation, and hyperparameter tuning.
- Experience with data engineering concepts: ETL/ELT, data partitioning, feature stores, SQL, and PySpark performance tuning.
- Familiarity with model lifecycle tooling: MLflow, version control (git), CI/CD pipelines, containerization (Docker), and cloud services (Azure, AWS, or GCP).
- Working knowledge of MedTech regulatory considerations (e.g., documentation for verification/validation, traceability, data privacy regulations such as HIPAA), and secure handling of clinical data.
Preferred qualifications
- BS/MS in Computer Science, Data Science, Statistics, Biomedical Engineering, or related field.
- Experience with time-series forecasting, REACT programming, Python
- Experience deploying models in commercial or medical device environments and running post-deployment monitoring for data drift, concept drift, and performance degradation.
- Experience with natural language processing (images, text, notes).
Technical stack (typical)
- Databricks (notebooks, jobs, Delta Lake, MLflow)
- Python, PySpark, pandas, NumPy
- Prophet, XGBoost, LightGBM
- SQL, PySpark performance tuning
- Cloud: Azure preferred
- REACT, JavaScript and SQL Server
- CI/CD tooling (Azure DevOps / GitHub Actions / Jenkins)
Human skills
- Strong problem-solving and debugging skills with attention to reproducibility and traceability.
- Clear communicator able to translate technical results for Commercial and Technology stakeholders.
- Collaborative team player, comfortable working across cross-functional teams (commercial, technology, business).
- High standards for data quality, documentation, and reproducible research practices.
Deliverables and success measures (examples)
- Production-ready Databricks pipelines that reliably prepare and serve feature data with automated tests.
- Predictive models with validated performance against pre-defined clinical acceptance criteria and documented validation artifacts.
- Automated regression tests that prevent unintended model degradations and reduce time-to-detect issues.
- Clear model performance and risk reports, and deployment of monitoring dashboards that detect drift and trigger remediation.
- Technical phone screen (Python, Databricks, ML fundamentals)
Preferred:
- Understanding of MedTech regulatory processes and GxP considerations is a plus.
- Builds a culture focused on customer outcomes and helping people and organizations succeed.
- Apply customer-centric discovery methods and build compassion with users.
- Advocates business agility and a fail-fast approach focused on measurable outcomes.
- Experience working with integrations, ERPs, and middleware technologies.
- Strong analytical and problem-solving skills; makes informed decisions under uncertainty.
For more information on how we support the whole health of our employees throughout their wellness, career and life journey, please visit www.careers.jnj.com.]
Required Skills:
Preferred Skills:
Advanced Analytics, Change Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Process Optimization, Relationship Building, Statistical Computing, Strategic Thinking
The anticipated base pay range for this position is :
$117,000.00 - $201,250.00
Additional 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
