At a Glance
- Tasks: Lead and develop Penta’s Data Science team while delivering impactful AI solutions.
- Company: Join a forward-thinking tech company focused on practical AI applications.
- Benefits: Enjoy competitive salary, generous time off, and a vibrant social culture.
- Other info: Dynamic team with excellent growth opportunities and hands-on leadership.
- Why this job: Shape the future of AI in a collaborative environment and make a real difference.
- Qualifications: 10+ years in applied AI, strong Python skills, and experience with LLMs.
The predicted salary is between 100000 - 150000 £ per year.
What’s in it for me?
- Competitive salary and compensation structure
- Generous paid time off and holiday schedule
- Frequent firm‑wide social events and activities
- Excellent environment for learning and growth
- Further benefits, depending on location
About The Role
We are looking for a hands‑on technical leader to lead Penta’s Data Science team: someone who still designs, builds and reviews real solutions while owning execution, delivery and team development. You will be accountable for turning data science capability into shipped, dependable value for our clients and advisory teams, in alignment with our product roadmap.
Penta’s technology makes client outcomes sharper, faster, more differentiated and harder to replace. The Data Science team’s success is measured by how much it improves live client work, not by technical elegance in isolation.
Our core data science focus is natural language understanding at scale, processing millions of articles daily across stakeholder sentiment, topic identification over time, competitive peer‑set selection, summarisation, contextualisation and other processing of unstructured content. Most use cases are creative chains of multiple steps drawn from data processing, exploratory analysis, fundamental ML, NLP, SQL, LLMs and integration into our live systems.
What You’ll Do
- Lead the team
- Manage, coach and develop Penta’s Data Science team, setting priorities, planning capacity and creating a high‑trust, high‑output delivery culture.
- Translate the product roadmap and advisory needs into a focused data science plan, partnering with Product, Advisory, Database, Development and DevOps teams to keep delivery aligned with client outcomes.
- Raise the delivery bar for execution, quality, pace, maintainability and cost discipline.
- Ship production data science and AI systems
- Design, build and review data science solutions across NLP, LLM workflows, machine learning, SQL and large‑scale content processing.
- Own technical design and architecture for data‑science‑enabled applications, ensuring solutions are maintainable, supportable, observable and easy to operate.
- Productionise delivery with DevOps and MLOps, automating deployment in AWS and putting evaluation, monitoring and provider‑routing controls in place so AI outputs remain reliable and cost‑effective.
- Scale practical AI adoption
- Design and implement AI workflows as skills, models and MCP tools in OpenWebUI, with cost control, provider routing and observability built in.
- Partner with other departments to turn AI capabilities into everyday workflows, reusable tools and knowledge layers that improve internal productivity and client delivery.
- Evaluate emerging AI tools, models and agentic patterns, bringing the useful ones into production quickly and responsibly.
Success in this role
Means the Data Science team is shipping reliable, maintainable AI and analytics capabilities into live client and advisory workflows; team members are growing; delivery is predictable; and Penta’s applied AI capability is visibly improving across products and engagements.
The Team
Our Technology team supports Penta’s ambitious delivery plans, using technology to automate solutions, optimise outcomes and support continuous integration and deployment. The six‑person Data Science team sits alongside Development, Engineering / DevOps & Platform Security, IT and the PMO, and works hand in hand with the Product team.
The environment is collaborative, pragmatic and delivery‑focused. We move quickly, share ideas openly, and use regular hackathons and experiments to generate practical business value.
This is the hands‑on leadership role for that team. Reporting to the CTO, you will lead a team working at the frontier of applied AI and data science, combining production LLM workflows, advanced prompting, agentic tooling, NLP, ML and large‑scale content processing. You will set its direction, raise its delivery bar, grow its people through hands‑on coaching, and lead from the front by actively shaping and delivering the work yourself.
Our approach to AI is practical
We are forward‑thinking and ambitious in practically applying AI across client‑facing work, corporate teams, technology and data science. We do not train our own foundation models; we apply, orchestrate and evaluate the best available models from major providers, engineering them into robust workflows that solve real business problems.
We validate and document our methodologies through white papers and technical explainers, setting out the academic and analytical foundations behind our products, and the evidence that supports their use. This helps build trust in our tools, why they work and shows how they can be applied.
We build on open‑source AI software, including LiteLLM and OpenWebUI, to maximise the internal value of AI and build durable institutional capability. Reliability, cost control, observability, instruction‑following, usability and adoption matter most.
The team designs reusable workflows, skills, models and MCP tools that support Penta’s move towards an AI‑native advisory operating system. Keeping Penta at the forefront of practical AI in PR, communications and strategic consultancy is part of the role.
About You
Tech skills required:
- Applied AI, LLMs and data science
- Advanced Python coding for data science
- Power‑user fluency with frontier AI tools, especially Claude: expert‑level prompting, context engineering, agentic workflows, model selection, evaluation, and practical use of the latest AI‑native data science techniques
- Practical experience engineering production LLM workflows, including prompt / skill design, evaluation, cost control, provider routing, agentic / human‑in‑the‑loop orchestration, embeddings, vector search and RAG
- Implementation of foundational ML algorithms, classic NLP techniques and LLMs
- Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation
- AWS: EC2, ECS, S3; DevOps and automated deployment
- Git version control
- Ideally experience with OpenWebUI, LiteLLM, MCP tools and/or Claude Code
Key competencies & experience
- Significant hands‑on experience as an Applied AI / Data Science technical leader, with recent, practical experience using frontier LLMs, prompting and agentic workflows to ship production systems. Typically this will mean around 10+ years’ hands‑on experience, with technical‑leadership exposure.
- A suitable degree, ideally in Software Engineering or a related technical field, and the technical grounding set out above will round out the profile.
The Successful Candidate Will Also Have
- An analytical and logical mind, dynamic, positive and ready to make a difference;
- The ability to communicate complex technical topics clearly to senior, non‑technical and technical audiences;
- A passionate drive for code quality, results and getting work shipped, with sound judgement on build‑vs‑buy, prioritisation and balancing speed against maintainability, cost and risk.
We strongly believe in developing talent and are willing to invest time to develop the people who join our team.
VP, Head of Data Science in London employer: Penta Group
Penta is an exceptional employer that fosters a collaborative and innovative work culture, providing ample opportunities for professional growth and development. With a competitive salary, generous paid time off, and a commitment to hands-on leadership, employees are empowered to make a meaningful impact in the field of data science while enjoying a vibrant social environment. Located in a dynamic tech hub, Penta offers unique advantages such as access to cutting-edge AI tools and a focus on practical applications that drive real business value.
StudySmarter Expert Advice🤫
We think this is how you could land VP, Head of Data Science in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Penta Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like VP, Head of Data Science at Penta Group.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Penta Group.
✨Apply Directly through Our Website
When you find a suitable opening like VP, Head of Data Science at Penta Group, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace VP, Head of Data Science in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Penta Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Penta Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Penta Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Penta Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
