• Full Time
  • London
  • Competitive


As an Audit practice, we invested significantly in innovative technology to understand how our client’s processes, technologies and systems operate to provide a fair view on how they address their risks. As part of PwC’s global strategy, The New Equation, we’re investing significantly in skills, capabilities and technologies to address the breadth and complexity of the challenges that our clients face with their businesses and in society. One of our responses to this was establishing Tech Central, a technology focused function working alongside other PwC teams. Technology is now at the heart of how our clients deliver their services. The complexity of systems, increasing use of data and the continuous investment in technologies by our clients, creates new challenges, but equally, opportunities, as to how we assess our client risks and build trust in society.
Embark on an exciting journey with PwC’s Digital Audit Business Unit as we launch the Generative AI Pod, a dynamic and innovative space dedicated to reshaping the future of audits through ground-breaking AI and Machine Learning technologies. Our startup-minded team aims to revolutionise auditing, collaborating closely with Audit Subject Matter Experts (SMEs) to drive innovation and advancements in how responsible AI can shape the future of Audit.

You will work alongside Tech Central, where building technology assets is one of their top priorities. You will build technology solutions in collaboration with other technical specialists including Agile Delivery Managers, Product Managers, Developer/s, Tester/s, Technical Architects as well as subject matter experts from wider Tech Central teams.

At the GenAI Pod, we’re pushing the boundaries of what’s possible.

As a Senior manager you will:

  • Lead the Generative AI Pod team and define the portfolio of projects
  • Lead as a technical SME the design and the implementation of various projects
  • Lead in developing strategic data science engagements with key clients in audit to form and execute the next development of pipeline opportunities
  • Lead and be accountable for the delivery of the GenAI Pod objectives working alongside our external and internal partners
  • Engineer scalable natural language models empowering auditors to efficiently analyse extensive document sets
  • Develop a vision for scalable solution from PoCs and MVPs
  • Automate audit processes through the application of AI, enhancing the identification of key risk indicators, patterns, and anomalies, ultimately elevating the precision and effectiveness of audit assessments
  • Be a role model while managing a team of data scientists and engineers on project and product teams
  • Support PwC’s growth opportunities

Preferred qualifications:

  • Masters or PhD in a data science-related discipline

Skills and Experience

  • A passionate and experienced data scientist, with a good technical understanding of Generative AI and LLMs
  • Understanding of requirements for software engineering and data governance in data science
  • Extensive experience with modern data platform architecture, experience in Deep Learning (PyTorch/TensorFlow)
  • Practical experience from industry and professional services in delivering large scale data platforms and valuable advanced analytics, blending large scale analytics and leveraging AI models
  • Ability to manage and coach a team of data scientists
  • Engagement with and management of technical and senior stakeholders
  • Strong knowledge of Mathematical Statistics, Algorithms & Data Structures, ML Theory
  • Strong knowledge of Python & SQL
  • Azure / GCP for cloud backend

Skills that will be beneficial but is not a prerequisite:

  • Experience working with large data pipelines (using technologies such as Beam or Kafka)
  • Experience in LLMs using OpenAI, Gemini or open source models
  • Exposure to other programming languages (such as Java)
  • Experience of working on a project using agile concepts (such as working in sprints)
  • Familiarity with working in an MLOps environment.
  • Experience working with search engines (such as Elasticsearch)


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