PwC
You can 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.
Working 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 teams.
Combining a passion for developing large scale platforms with a keen interest in data science, you will work alongside data scientists to develop scalable solutions, moving products from Proof of concepts to Minimal Viable products.
At the GenAI Pod, we’re pushing the boundaries of what’s possible.
As a Manager you will:
- Lead in developing strategic data science engagements with key clients in audit to form & execute the next development of pipeline opportunities
- Lead and be accountable for the delivery of core data science assets (such as SaaS platforms) in client facing settings
- Engineer scalable natural language models empowering Auditors to efficiently analyse extensive document sets.
- 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.
- Scale out natural language processing models to identify and make predictions over vast datasets.
- Be a role model while managing a team of data scientist and engineers on project and product teams
- Support PwC’s growth opportunities
Skills and Experience
We want people who are passionate about data science Engineering and who have invested time in understanding Generative AI and experienced the power of LLM
- 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
- Engagement of technical and senior stakeholders
- Ability to manage and coach a team of data scientists
- Understanding of requirements for software engineering and data governance in data science
- Experience in Data engineering role with a level of experience on deploying ML solutions and leading Data science/Engineering teams.
- Extensive experience with modern Data platform architecture, experience in Deep Learning (PyTorch/TensorFlow)
- Strong knowledge of Mathematical Statistics, Algorithms & Data Structures, ML Theory
- Strong knowledge of Python & SQL
- Strong debugging skills
- Git for version control
- Azure / GCP for our cloud backend
Skills that will be beneficial but 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)
- Bachelor’s degree (or more) in computer science / Data Science or a related technical discipline
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