Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist-Manager

PwC UK
Reading
2 days ago
Create job alert
About The Role

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’re recognised 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’re looking for self‑starting, progressive, and inquisitive individuals who want to shape the future of how AI is applied in real business contexts. You’ll join a collaborative and entrepreneurial team that combines deep technical expertise with 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.


Key Responsibilities

  • Work 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) to Agentic AI.
  • Design and advise on the data‑science approach for your product, balancing rigor, interpretability, and scalability, and ensuring models are reusable across multiple client contexts.
  • Partner with sector and go‑to‑market teams and solution architects to identify client challenges, demonstrate product capabilities, gather feedback, and inform development priorities.
  • Collaborate closely with engineers to productionise models on cloud platforms (Azure, AWS, or GCP) using MLOps and DevSecOps practices.
  • Work with the product owner to monitor model performance and user feedback, continually refining algorithms, enhancing feature design, and improving product outcomes over time.
  • Embed responsible and explainable AI principles into development so outputs are trusted, transparent, and compliant with PwC’s standards.

Skills & Experience

  • Demonstrable practical project experience (professional or academic) in applying analytics to solve business problems.
  • 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.
  • Strong data‑storytelling and visualisation skills, with the ability to explain complex data concepts clearly to technical and non‑technical audiences.
  • Intellectual curiosity with a disciplined, hypothesis‑led approach to validating, challenging, and refining outputs.
  • Commercial curiosity and a desire to understand how analytics drives business outcomes.
  • Collaborative mindset and experience working in diverse cross‑functional teams.

Job Details

  • Seniority level: Entry level
  • Employment type: Full‑time
  • Job function: Engineering and Information Technology
  • Industries: Accounting
  • Location: Reading, England, United Kingdom
  • Salary: £28,000.00 per year (fixed)


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.