AddressOur purpose focuses on how we contribute to society, and how our business decisions can contribute to greater trust and solving important problems. In order to achieve our purpose and deliver a first-class service to our clients, we need first-class support internally. The people who power us - our internal teams - have a vital role to make sure we have all the right resources, services and technology to be the best we can be. Not all of us work directly with external clients.
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.
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.
About the team
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.
The Role
At the GenAI Pod, we’re pushing the boundaries of what’s possible. As a Senior Associate in our GenAI Lab start-up, you will:
Pioneer the design, development, and deployment of production machine learning pipelines
Shape machine learning-enabled, Audit applications
Deliver high-quality code contributions to our evolving codebase
Monitor and review live production models
Lead and guide workstreams on projects within your specialisation
Mentor and manage junior engineers on impactful workstreams
Skills and Experience
A passionate data scientist, who has invested time in understanding Generative AI and experienced the power of LLM
Practical experience from industry and professional services in delivering significant and valuable advanced analytics projects and/or assets
Engagement of technical and senior stakeholders
Ability to manage and coach a team of data scientists
Delivery of projects on time and in budget for high profile clients
Understanding of requirements for software engineering and data governance in data science
We make extensive use of the following technologies in our team. We expect you to be fluent with using these tools and practices on a daily basis.
Bachelor's degree (or more) in computer science / Data Science or a related technical discipline
3+ years of experience in Natural Language Processing
Extensive experience with modern Deep Learning (PyTorch/TensorFlow)
Experience with any of the following NLP tasks - named entity recognition, intelligent document processing, website parsing & classification, sentiment analysis, information retrieval, entity matching & linking, spelling correction
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 we’d like to hear about
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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