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Senior Scientist, Discovery Data Science

LinkedIn Johnson & Johnson Innovative Medicine Spring House, PA
Not Applicable Posted March 26, 2026 Job link
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Requirements
  • PhD in Data Science, Computational Science, or a related drug‑discovery field, with strong, hands‑on expertise in data science, machine learning, and modern AI approaches.
  • Proven ability to design, evaluate, and customize deep learning architectures to tackle complex scientific challenges and deliver innovative, high‑impact solutions.
  • Proficiency in Python, with experience using major deep‑learning frameworks such as PyTorch, TensorFlow, or Keras, and strong working knowledge of scientific libraries (NumPy, SciPy, Pandas).
  • Experience or affinity with cloud computing and MLOps practices is highly valued.
  • Experience in data analytics, predictive modeling, and AI-assisted‑assisted molecular design and optimization for small molecules (desired).
  • Experience applying AI/ML to off-t‑target risk prediction or liability modeling in drug discovery (desired).
  • Familiarity with biology and/or chemistry, and enthusiasm for learning across scientific domains (desired).
  • Demonstrated ability to thrive in cross‑functional, matrixed project teams, contributing effectively to multidisciplinary research.
  • A track record of planning, executing, and delivering complex scientific projects, with strong analytical thinking and scientific rigor.
  • Genuine passion for applying computational science to real‑world industrial problems, especially in the context of improving human health through drug discovery.
  • Strong communication, organizational, and interpersonal skills, including the ability to collaborate, present results clearly, and engage with diverse scientific partners.
  • A commitment to being part of a team that values diversity, fosters inclusion, and encourages creativity, innovation, and continuous learning.
  • Any earlier experience in AI-driven molecular design and optimization, related predictive modelling, data analytics or liability modelling, or exposure to applied biology or chemistry would strengthen an application.
Preferred Skills
  • Experience or affinity with cloud computing and MLOps practices is highly valued.
  • Experience applying AI/ML to off-t‑target risk prediction or liability modeling in drug discovery (desired).
  • Familiarity with biology and/or chemistry, and enthusiasm for learning across scientific domains (desired).
  • Any earlier experience in AI-driven molecular design and optimization, related predictive modelling, data analytics or liability modelling, or exposure to applied biology or chemistry would strengthen an application.
  • Advanced Analytics, Business Intelligence (BI), Coaching, Collaborating, Critical Thinking, Data Analysis, Database Management, Data Privacy Standards, Data Reporting, Data Savvy, Data Science, Data Visualization, Econometric Models, Process Improvements, Technical Credibility, Technologically Savvy, Workflow Analysis
Education
  • (Not required) – PhD in Data Science, Computational Science, or a related drug‑discovery field, with strong, hands‑on expertise in data science, machine learning, and modern AI approaches.
  • (Not required) – Advanced Analytics, Business Intelligence (BI), Coaching, Collaborating, Critical Thinking, Data Analysis, Database Management, Data Privacy Standards, Data Reporting, Data Savvy, Data Science, Data Visualization, Econometric Models, Process Improvements, Technical Credibility, Technologically Savvy, Workflow Analysis