Data Scientist-Manager

Line of Service

Advisory

Not Applicable

Organisation Strategy

Manager

PwC’s Data & AI Consulting team is rapidly expanding as we invest in building a new generation of Artificial Intelligence (AI) products that transform how we deliver value to our clients.

We’rerecognised by industry analysts, such as Gartner and IDC, as a market-leading Data & AI services consultancy and are actively working with clients to design,develop and deliver AI-powered products and data capabilities that achieve tangible outcomes and business value.

We’relooking for self-starting, progressive, and inquisitive individuals who want to shape the future of how AI is applied inreal businesscontexts.

You’lljoin a collaborative and entrepreneurial team that combines deep technicalexpertisewith sector knowledge and product thinking. We work in cross-functional squads to design, build, and launch solutions that create measurable impact for our clients and strengthen PwC’s position as a leader in trusted, responsible AI.

If you want to apply your skills to complex challenges, help define new products, and be part of an ambitious teamthat’sre-imagining the role of AI in professional services, this could be the role for you.

• Working as part of a cross-functional product squad - including AI Engineers, Product Designers, Data Scientists and Industry Sector Specialists - to launch and scale AI client solutions, from core data science products (e.g. pricing and forecasting) all the way through to Agentic AI
• Designing and advising on the data science approach for your product, balancing rigour, interpretability, and scalability, and ensuring models are reusable across multiple client contexts
• Partnering with sector and go-to-market teams and solution architects toidentifyclient challenges,demonstrateproduct capabilities, gather feedback, and inform development priorities
• Collaborating closely with engineers to product ionise models on cloud platforms (Azure, AWS, or GCP) usingMLOpsand Dev Sec Ops practices
• Working with the Product owner tomonitoringmodel performance and user feedback to continuously refine algorithms, enhance feature design, and improve product outcomes over time
• Embedding responsible and explainable AI principles into development to ensure outputs are trusted, transparent, and compliant with PwC’s standards

• Practical experience across the data science lifecycle - from feature engineering and model design to validation, deployment, and monitoring;
• Fluency in Python, SQL, or similar programming languages;
• Experience using deep learning frameworks such as Tensor Flow,Keras,PyTorch, orMXNet;
• Familiarity with Agile andDev Sec Ops practices , including use of Git for version control;
• Exposure to cloud environments (Azure,AWSor GCP) and a desire to build solutions that scale;
• The ability to explain complex data concepts clearly to technical and non-technical audiences, with strong data storytelling and visualisation skills;
• Intellectual curiosity with a disciplined, hypothesis-led approach - validating, challenging, and refining your outputs to ensure analytical rigour and business relevance
• Commercial curiosity and the desire to understand how analytics drives business outcomes;
• A collaborative mindset - you enjoy working in diverse, cross-functional teams that have a blend of onshore and offshore resources

• 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.
• 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
• much more

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Artificial Intelligence, Big Data, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data-Driven Decision Making (DIDM), Data Engineering, Data Lake, Data Mining, Data Modeling, Data Pipeline, Data Quality, Data Science, Data Science Algorithms, Data Science Troubleshooting, Data Science Workflows, Deep Learning, Embracing Change, Emotional Regulation {+ 22 more}

Up to 60%

No

No

November 23, 2025