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For Companies At a Glance
- Tasks: Lead AI projects, mentor a team, and deliver impactful data science solutions.
- Company: Fast-scaling AI consultancy known for technical excellence and real-world impact.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a collaborative team and shape the future of AI in regulated industries.
- Qualifications: Experience in machine learning, strong Python skills, and team leadership.
- Other info: Dynamic environment with a focus on innovation and strategic value creation.
The predicted salary is between 43200 - 72000 ÂŁ per year.
This is a leadership opportunity at a fast‑scaling AI consultancy known for its technical excellence and track record in delivering real‑world impact across highly regulated industries. The team helps major clients in finance, insurance, legal, and other sectors apply cutting‑edge data science in complex operational environments, balancing innovation with reliability and rigor.
You’ll join a deeply technical, collaborative group working on custom AI and machine learning solutions that support automation, forecasting, and decision intelligence. The focus is on strategic value creation: solving ambiguous problems with clarity, and delivering tools that embed into the heart of client systems.
What You’ll Be Doing
- Set the technical direction on multi‑disciplinary data science & AI projects, from approach selection to architecture design.
- Take ownership of full solution pipelines, leading hands‑on development and supporting others to do the same.
- Work closely with senior client stakeholders to shape project scope, track value delivery, and communicate findings.
- Oversee a small team of data scientists on each project, supporting mentorship, quality control, and technical review.
- Collaborate with commercial and delivery teams to shape proposals and ensure feasibility of engagements.
- Contribute to internal capability‑building by sharing knowledge, tools, and best practices within the wider team.
What They’re Looking For
- Led the delivery of applied machine learning projects, ideally across commercial or regulated sectors.
- Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch.
- Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, NLP, and LLM/GenAI projects.
- Ability to scope and structure solutions around ambiguous business problems, turning them into tractable pipelines.
- Confident in managing small technical teams, reviewing work, and setting standards for robustness and clarity.
- Experience with stakeholder engagement and translating outputs for non‑technical audiences.
If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via (feel free to include a CV for review).
Location: London, England, United Kingdom
Principal Data Scientist in England employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist in England
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Principal Data Scientist role.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving machine learning and AI. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your past projects and how you've tackled complex problems. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Principal Data Scientist in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal Data Scientist role. Highlight your leadership in data science projects and any relevant technical expertise, especially in Python and machine learning.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've tackled ambiguous problems and delivered impactful solutions in previous positions.
Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! Mention your experience with core libraries like NumPy and Pandas, and any familiarity with deep learning tools. We want to see your hands-on experience shine through.
Engage with Us: If you have questions or want to discuss your application, feel free to reach out! We love hearing from potential candidates. Remember, applying through our website is the best way to get your foot in the door.
How to prepare for a job interview at Xcede
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description, especially Python and its libraries like NumPy and Pandas. Brush up on your knowledge of machine learning methods and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Leadership Skills
Since this role involves overseeing a small team, be prepared to share examples of how you've successfully managed projects and mentored others. Highlight your experience in leading hands-on development and ensuring quality control in your previous roles.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms. You’ll need to demonstrate your ability to engage with senior client stakeholders and translate your findings for non-technical audiences, so think of examples where you’ve done this effectively.
✨Prepare for Problem-Solving Questions
Expect to tackle ambiguous business problems during the interview. Prepare to discuss how you would scope and structure solutions, turning vague challenges into clear, actionable pipelines. Use past experiences to illustrate your thought process and problem-solving skills.