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# Lead Data Scientist

- **Company:** Johnson & Johnson
- **Location:** New Brunswick, NJ, United States (Remote available)
- **Experience:** Expert
- **Salary:** $140,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Discrete Event Simulation, Graph Database, Python (Programming Language), Monte Carlo Methods, Neo4j, Software Systems, SQL Databases, Tableau (Software), Modeling and Simulation
- **Published:** August 15, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pb8squxbv9

## About the Role

Requirements: Employer will accept a Master's degree in Industrial Engineering, Operations Research, Data Science, or related field and 4 years of experience in the job offered or in a Lead Data Scientist-related occupation.

Position Requires Experience With

 * Healthcare industry manufacturing and supply chain processes;
 * Supply chain analytics including requirements gathering for advanced analytics solutions;
 * Mathematical optimization and queueing theory;
 * Stochastic simulation, Monte Carlo simulation, and Discrete Event simulation techniques;
 * Python, SQL, SIMIO and Tableau;
 * Graph database (Neo4j); and
 * Data science product design.

## Description

Job Duties: Perform Advanced System Simulation and Optimization Modeling supporting design of large and complex pharmaceutical and medical device supply chains using advanced operations research models. Design data science solutions based on gathering and translation of business requirements. Integrate models into E2E production strength solutions which can be deployed for use by business users. Develop new algorithms and mathematical models for supply chain optimization of manufacturing and distribution sites. Analyze and de-bottleneck supply chains using stochastic, and statistical models. Deploy supply chain optimization software solutions built by coding in Python, SQL and Tableau. Develop End to End supply chain network simulation models using SIMIO tool for high volume pharma and medical device products and analyze potential risk associated in delivering products on time. Develop supply chain digital twin using graph databases in Neo4j.


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