Data Scientist and Application Developer

Johnson & Johnson Johnson & Johnson · Pharma · Latina, Italy

Seeking a Data Scientist and Application Developer to build internal web applications for analytics and operationalize models for product quality decisions in a GMP context. The role involves developing services with Python (Flask/FastAPI), implementing software engineering practices, applying statistical and modeling fundamentals to manufacturing data, and collaborating with cross-functional teams in a regulated environment.

What you'd actually do

  1. Build and maintain internal web applications that make analytics usable in day-to-day workflows.
  2. Develop services using Python with Flask (and/or FastAPI where appropriate), including: Lightweight APIs for data access and model execution User-facing interfaces using Flask + Jinja, with small amounts of JavaScript and optionally React for richer interactions.
  3. Apply strong fundamentals in statistics, data extraction + cleaning, and modeling to diverse manufacturing datasets (e.g., batch/process time series, quality data, laboratory and instrument outputs).
  4. Develop, evaluate, and document models intended to support insights into manufacturing performance in a GMP environment, focusing on interpretability and lifecycle considerations.
  5. Use git fluently in a team setting (branches, pull requests, code reviews).

Skills

Required

  • Bachelor’s degree (or higher) in Data Science, Statistics, Computer Science, Engineering, or related field (or equivalent practical experience).
  • Strong data science fundamentals: Basic statistics and experimental reasoning Data wrangling and exploratory analysis Model building and evaluation.
  • Strong Python skills for both analysis and application development.
  • Familiarity with basic SQL fundamentals is required.
  • Experience building user-facing applications using Flask (templates/Jinja) and familiarity with basic front-end concepts (HTML/CSS/JavaScript).
  • Comfort working with diverse, imperfect datasets and iterating toward robust solutions.
  • Strong collaboration and communication skills in a cross-functional environment.

Nice to have

  • Familiarity with FastAPI and API design concepts (can be learned on the job if needed).
  • Experience supporting software or analytics in regulated/GMP-like environments (validation mindset, documentation discipline, traceability).
  • Exposure to manufacturing, pharma, chemical, or other industrial process data.
  • Knowledge of Azure services and/or identity concepts (e.g., Entra ID) is a plus but not required.
  • Familiarity with containerization/DevOps practices (e.g., Docker, CI/CD) is helpful.

What the JD emphasized

  • GMP context
  • GMP environment
  • regulated context
  • regulated and non-regulated use
  • regulated/GMP-like environments

Other signals

  • operationalizing models
  • inform product quality decisions
  • interpretability
  • lifecycle considerations
  • regulated context