Data Science Consultant for transformation AI/ML projects @ Deloitte

6 days ago

Prague, Czech Republic Deloitte Full time

🔎What we’re looking for:

  • We're seeking early-career professionals with 1-2 years of hands-on experience in data science, analytics, or machine learning projects that create real business impact.
  • Solid Python skills, plus familiarity with cloud platforms (Azure, GCP, or AWS)
  • Ability to connect technical solutions with business needs and communicate both ways effectively
  • Exposure to the AI/ML lifecycle - from business problem definition to model deployment
  • Curiosity and interest in Generative AI and its real-world applications
  • Strong English communication skills
  • EU work permit and willingness to travel within the region

Nice to have:

  • Experience in consulting or client-facing roles.
  • Exposure to MLOps, model governance, or AI risk frameworks.
  • Understanding of enterprise architecture and data platforms

What we offer:

  • You can look forward to:
  • A performance-based annual bonus to recognize your contribution
  • A hybrid way of working
  • A flexible benefits program to support your lifestyle, health, and personal interests
  • Additional paid time off and flexible sick leave options
  • Financial support during important life events, such as illness or parental leave
  • Comprehensive insurance coverage for both business and personal travel
  • Company-provided equipment and tools to help you succeed
  • Opportunities for professional growth through external and internal training
  • Access to sports, wellness, and cultural activities, plus modern facilities at work
  • Regular team events and a friendly, collaborative environment



,[Consult on AI strategy: Help clients define what AI should deliver for their business and how to organize around it., Deliver value-focused data science: Build and deploy ML models that solve real business problems, not just technical challenges., Shape operating models: Design how AI teams should work, collaborate, and scale within enterprise environments., Support governance and risk: Advise on responsible AI practices, model validation, and compliance., Collaborate across disciplines: Work with business stakeholders, data engineers, and architects to ensure solutions are practical and scalable., Stay pragmatic: Simplify complex concepts to drive adoption and impact.] Requirements: Data science, Machine learning, Python, Cloud platform, AWS, GCP, Azure, AI, MLOps, Enterprise Architect, Data platforms

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