Principal- AI and Data Sciences

At Johnson & Johnson,we believe health is everything.

Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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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We provide an inclusive work environment where each person is considered as an individual.

At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

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
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