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For Companies At a Glance
- Tasks: Join a dynamic team to launch and scale innovative AI solutions.
- Company: Leading firm focused on cutting-edge data science and AI technologies.
- Benefits: Flexible working, private medical cover, and generous volunteering days.
- Why this job: Make a real impact with AI while collaborating with diverse teams.
- Qualifications: Experience in data science, Python, and cloud platforms required.
- Other info: Great opportunities for career growth and personal development.
The predicted salary is between 28800 - 48000 £ per year.
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 monitor 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 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.
Data Scientist-Manager in London employer: PwC
Contact Detail:
PwC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist-Manager in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data science field. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Create a portfolio showcasing your projects and skills. Whether it’s a GitHub repository or a personal website, make sure you highlight your experience with Python, SQL, and any deep learning frameworks you’ve used. This is your chance to shine!
✨Ace the Interview
Prepare for interviews by practicing common data science questions and scenarios. Be ready to explain your thought process and how you approach problem-solving. Remember, they want to see your analytical skills in action!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist-Manager in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist-Manager role. Highlight your practical experience across the data science lifecycle and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our cross-functional product squad. Don't forget to mention your experience with AI solutions and cloud platforms!
Showcase Your Technical Skills: Be sure to include your fluency in Python, SQL, and any deep learning frameworks you've used. We want to see how you've applied these skills in real-world scenarios, so share specific examples!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at PwC
✨Know Your Data Science Lifecycle
Make sure you can talk confidently about your experience across the entire data science lifecycle. Be ready to discuss specific projects where you've handled feature engineering, model design, validation, deployment, and monitoring. This shows you understand the role's requirements and can hit the ground running.
✨Showcase Your Technical Skills
Brush up on your Python, SQL, and any deep learning frameworks you've used like TensorFlow or PyTorch. Be prepared to give examples of how you've applied these skills in real-world scenarios. This will demonstrate your technical prowess and ability to contribute to the team immediately.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You might be asked to present a past project or solution, so focus on your data storytelling and visualisation skills. Being able to communicate effectively with both technical and non-technical audiences is crucial for this role.
✨Emphasise Collaboration
Highlight your experience working in cross-functional teams. Share examples of how you've partnered with engineers, product owners, and other stakeholders to achieve common goals. This will show that you're not just a lone wolf but someone who thrives in a collaborative environment.
