VP, Head of Data Science

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 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: 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.