Senior Data Scientist - Global Scale Up

Senior Data Scientist | AI Start-up | Northern Ireland (Remote-First) Senior individual contributor role in a fast-growing, AI-first scale-up Northern Ireland based, remote-first working £95,000 to £140,000 plus equity and comprehensive benefits Hands-on across the full lifecycle: data, modelling, evaluation and production Work on LLM and agent-based systems used by global enterprise clients The Company Our client is a venture-backed technology company building an agentic AI platform used by some of the world's largest enterprises.

Their AI agents learn, adapt and scale to replace brittle, manual processes with resilient automation, helping customers ship software faster and with greater confidence. It is a small, highly capable team with a culture built on intellectual curiosity, where people are trusted with real ownership and expected to get stuck in wherever the work takes them.

The Role This is a genuinely broad Senior Data Scientist role for someone who is equally comfortable interrogating data, building models and getting them working reliably in production. You will sit at the centre of the data science function, taking models and agentic workflows from exploratory work through to robust, monitored production systems, while also shaping how the team measures the quality of its LLM and agent-based products.

In a small team, breadth matters as much as depth. You will regularly step outside your core specialism to cover ground for colleagues, so this role suits someone with a varied background who enjoys rolling up their sleeves, whether that means data wrangling, statistical analysis, pipeline engineering or production troubleshooting. You will also bring a pragmatic, delivery-focused mindset: knowing when something is good enough to ship and when it needs further refinement.

Key Responsibilities Build and train ML models hands-on, from exploratory analysis and feature engineering through to validated, production-ready solutions Design and maintain reliable, reproducible pipelines for training data, feature generation and embeddings Develop evaluation frameworks and metrics for LLM and agent-based systems, covering accuracy, safety, latency and cost Build automated scoring, regression testing and LLM-as-judge approaches that catch quality drops before they reach production Own the reliability of models and agents in production, including CI/CD, versioning, monitoring, drift detection and rollback Analyse failure modes and edge cases, using sound statistical reasoning to prioritise fixes Make cost-aware technical decisions, balancing performance against infrastructure spend in a start-up environment Cover ground across the team when needed, adapting quickly to changing priorities and product pivots Contribute to the data and ML platform roadmap and help set engineering standards Mentor and support colleagues, and communicate technical trade-offs clearly to non-technical stakeholders Essential Requirements 5 years' experience in data science, ML engineering or a closely related field, ideally across more than one domain or industry A strong mathematical and statistical foundation, with hands-on experience building and evaluating models yourself Proven experience taking ML models into production, including pipelines, deployment and monitoring Strong Python skills and solid software engineering fundamentals Practical experience with LLMs and modern techniques such as prompting, retrieval and agentic workflows

Experience with Google Cloud Platform (Vertex AI, Big Query) or an equivalent major cloud ML platform Familiarity with ML tooling such as MLflow, Kubeflow or Sage Maker, plus Docker and Kubernetes Comfortable working in a fast-moving, resource-conscious environment where you…