User Researcher ofertas em Grã-Bretanha

The Data & AI capability within Tech Catalyst builds and deploys advanced AI solutions that solve hard problems for PwC and for its clients.

Our team works at the frontier of AI and ML in professional services. We work across multiple industries, including healthcare, financial services, and professional services such as audit.

We are looking for people to contribute to the development of AI tools and solutions, and help the business build capabilities on cutting-edge AI and NLP techniques to aid better decision making via agents, intelligent workflow automation and decision intelligence.

We're currently looking for a motivated, self-starter individual, comfortable with ambiguity, and willing to lead and technically contribute to the design, prototyping, and delivery of AI systems in a cross-functional environment, with 6+ years of experience in data science, to join us across our Manchester, Leeds, Birmingham, and London offices.

• Solution Development: Contribute to designing, developing and scaling AI and NLP solutions addressing specific business problems or opportunities. This involves understanding business requirements, assessing feasibility, selecting appropriate techniques and technologies, and creating scalable and efficient solutions.
• AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. This includes staying updated on AI trends and advancements, conducting market research, and providing recommendations on AI adoption and implementation.
• Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. This includes selecting appropriate algorithms, optimising model performance, conducting experiments and testing, and ensuring that the models meet the desired accuracy, reliability, and performance criteria.
• Collaboration and Stakeholder Management: Help the wider team collaborating with business stakeholders, technology teams, and other relevant groups to understand their needs, gather requirements, and align AI solutions with organisational goals.
• Prototyping, developing, and deploying machine learning applications into production
• Contributing to our machine learning enabled, business-facing applications
• Contributing effective, high quality code to our codebase
• Model validation and model testing of production models
• Presenting findings to senior internal and external stakeholders in written reports and presentations
• Leading work and small teams, with the ability to coach, mentor, and set technical direction

• Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow)
• Experience with containerization (e.g. Docker)
• Evidence of application of statistics (e.g. evaluating AI implementations)
• Understanding of machine learning techniques and application to real world problems
• Experience with data manipulation libraries (e.g. Pandas, Spark, SQL)
• Problem solving skills
• Git for version control
• Cloud experience (we use Azure/GCP/AWS)

• Evidence of modelling experience applied to industry relevant use cases
• Evidence of designing and implementing LLM, RAG and agentic solutions
• Experience in deployment at scale (e.g. Kubernetes)
• Familiarity with working in an MLOps environment
• Familiarity with optimisation and simulation techniques

No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications not specified

• Accepting Feedback
• Active Listening
• Analytical Thinking
• Artificial Intelligence
• Big Data
• Data Engineering
• Data Modeling
• Data Pipeline
• Data Quality
• Data Science
• Data Science Algorithms
• Data Science Workflows
• Deep Learning
• Embracing Change
• Git
• Machine Learning
• Python
• SQL
• Version Control
• Cloud (Azure/GCP/AWS)

• Evidence of modelling experience applied to industry relevant use cases
• Evidence of designing and implementing LLM, RAG and agentic solutions
• Experience in deployment at scale (e.g. Kubernetes)
• Familiarity with working in an MLOps environment
• Familiarity with optimisation and simulation techniques

Yes

No