Principal- AI and Data Sciences

Johnson & Johnson Innovative Medicine•Irvine, CA

6d•$117,000 - $201,250•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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).
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.

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

Benefits

Consolidated retirement plan (pension)
Savings plan (401(k))
Vacation –120 hours per calendar year
Sick time - 40 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 period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year