Principal- AI and Data Sciences

Johnson & Johnson
Johnson & Johnson logo
Location
Irvine, California, United States of America
Job Type
Full-time
Posted
September 25, 2026
Views
48
Salary Range
$117k - $201k USD

Job Description

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 atjnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. 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

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.

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 atjnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. 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

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 visitwww.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

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Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Irvine, California, United States of America. The posting notes the position will be in Irvine, CA and Raritan, NJ, and requires up to 25% travel. A specific remote, hybrid, or on-site work-mode policy is not mentioned.
What are the required qualifications and experience level for this role?
You need 2–3 years of professional AI/ML or data science engineering experience in MedTech or a regulated healthcare environment. Required skills include hands-on Databricks experience, proficiency in Python and common ML libraries (Prophet, PySpark, XGBoost/LightGBM, Hugging Face), and experience building prediction models for structured and unstructured data.
What are the key responsibilities of the Principal AI and Data Sciences?
You will design, build, and maintain end-to-end ML solutions on Databricks, implement data pipelines using Spark/PySpark, develop and optimize supervised/unsupervised models, establish regression test suites, apply model explainability techniques, and package/register models using MLflow. You will also troubleshoot production issues and integrate models using Agentic frameworks and APIs.
What is the salary range for this position?
The anticipated base pay range for this position is $117,000.00 - $201,250.00.
What benefits and time-off policies are offered?
Benefits include a consolidated retirement plan (pension) and a 401(k) savings plan. Time-off benefits include 120 hours of vacation, 40-56 hours of sick time, 13 holiday/floating holiday days, 480 hours of parental leave, bereavement leave, caregiver leave, volunteer leave, and military spouse time-off.

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Job Information

Source: workday
AI Relevance: 90/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Irvine, California, United States of America
Skills & Tags:
johnson & johnson pharma
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