Data Scientist-Manager

PwC
London
1 month ago
Create job alert

the role

for you. 

What your days will look like:

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 to identify client challenges, demonstrate product capabilities, gather feedback, and inform development priorities 

Collaborating closely with engineers to productionise models on cloud platforms (Azure, AWS, or GCP) using MLOps and DevSecOps practices 

Working with the Product owner to monitoring model 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 

This role is for you if:

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 TensorFlow, Keras, PyTorch, or MXNet; 

Familiarity with Agile and DevSecOps practices, including use of Git for version control;

Exposure to cloud environments (Azure, AWS or 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 

What you’ll receive from us:

No matter where you may be in your career or personal life, our 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.


Related Jobs

View all jobs

Data Scientist

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist - Measurement Specialist

Data Scientist (Predictive Modelling) – NHS

Data Scientist

Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.