Head of Data Science

Beamery

full-time

Posted on: 9/18/2025

Origin: • 🇬🇧 United Kingdom

✨ AI Apply

Lead

CloudDockerGoogle Cloud PlatformKubernetesMongoDBPythonPyTorchSQL

About the role

Define and implement the company’s AI and data science strategy aligned with product vision and commercial priorities
Serve as a key connector between the C-suite and the data organization; communicate strategy, progress, risks, and opportunities to executives
Collaborate with Product, Engineering, and Commercial leadership to translate data capabilities into business outcomes
Oversee full lifecycle delivery of AI project portfolio from research through production across personalization, recommendation, analytics, and automation
Lead development of AI systems including scaling the company’s Knowledge Graph and building agentic models to create new product experiences
Lead, grow, and support a world-class, multi-disciplinary data team across data science, applied ML/AI, and knowledge engineering
Foster a culture of clarity, curiosity, and shared success balancing research with customer-focused delivery
Implement and maintain governance, ethics, and compliance frameworks for AI systems
Represent Beamery externally as a thought leader in AI and data science

Proven experience leading multi-disciplinary teams at scale (10+ people across data science, ML, engineering, knowledge graph/ontology, and AI)
Strong track record of delivering AI-driven products in complex B2B or enterprise SaaS environments
Expertise in engaging and communicating with senior stakeholders
Strategic mindset paired with pragmatic approach; comfortable navigating ambiguity and making trade-offs
Solid grounding in applied ML/AI technologies (e.g., LLMs, graph learning, recommendation systems, optimization)
Experience with knowledge graphs, entity resolution, graph-based embeddings, and search
Technical familiarity with Python, Agentic tools (Autogen, Semantic Kernel, LangChain), SQL, MongoDB, third-party LLM APIs, LiteLLM, MLflow, GCP, Docker, PyTorch, Hugging Face Transformers, SPARQL, Kubernetes
Passion for building mission-driven teams that combine research excellence with commercial delivery
Ability to lead, grow, and support multi-disciplinary teams across data science, applied ML/AI, and knowledge engineering
Willingness/ability to work hybrid from London office (office days specified)