Associate Principal AI Data Scientist
Workplace: Göteborg, Sverige
Expires: August 28, 2025
Join AstraZeneca as an Associate Principal AI Data Scientist to drive innovation in agentic AI, multi-agent systems, and HITL multi-agent systems, transforming drug development through advanced data science methods and AI strategies. This role supports pharmaceutical development projects to deliver effective and groundbreaking medicines.
Main requirements:
  • Advanced degree in computer science, data science, AI, machine learning or related fields.
  • Expertise in designing multi-agent patterns, digital twins and agentic AI design patterns.
  • Proven industrial experience in reinforcement learning and applied machine learning domains such as deep learning, causal ML, transfer learning.
  • Excellent coding skills in Python and R.
  • Hands-on industrial experience with AI/ML frameworks like TensorFlow and PyTorch.
  • Experience with generative AI orchestration frameworks such as LangGraph and CrewAI.
Responsibilities:
  • Drive innovation in agentic AI, multi-agent systems, and digital twins by exploring new methodologies and applications.
  • Design, implement, and optimize algorithms for autonomous decision-making, coordination, and policy learning among agents and digital twins.
  • Evaluate agent performance considering decision making, collaboration, competition, and uncertainty.
  • Lead machine learning initiatives in drug development projects.
  • Collaborate with cross-functional teams and ensure knowledge transfer to IT engineering for solution build and deployment.
  • Keep updated with industry advances by reviewing academic literature and participating in conferences.
  • Publish scientific findings and represent the company in scientific forums.
  • Communicate technical concepts and results effectively to diverse audiences.
Required hard skills:
  • Advanced degree in relevant fields (computer science, AI, data science).
  • Programming in Python and R.
  • Designing multi-agent systems and agentic AI.
  • Reinforcement learning.
  • Usage of AI/ML frameworks (TensorFlow, PyTorch).
  • Experience with GenAI orchestration frameworks (LangGraph, CrewAI).
  • Applied machine learning in domains such as deep learning, causal ML, transfer learning.
Recommended hard skills:
  • Contributions to open-source projects (highlight GitHub PRs).
  • Strong publication record in AI.
  • Experience in pharmaceutical sector multi-agent system design.
  • Machine learning applications in pharmaceutical development, chemical engineering, or chemistry.
  • Experience with federated learning, few/zero shot learning, meta learning, explainable AI.
Soft skills:
  • Innovative thinking
  • Collaboration and cross-functional teamwork
  • Effective communication with technical and non-technical audiences
  • Adaptability and continuous learning
  • Ability to work independently as individual contributor
Coding languages:
  • Python
  • R
Frameworks:
  • TensorFlow
  • PyTorch
  • LangGraph
  • CrewAI
Natural languages:
  • English (Proficient)
Cultural skills:
  • Embraces change
  • Patient- and business-centric mindset
  • Sharing learnings to scale innovations
  • Flexibility balancing office presence and remote work