Data Scientist – GenAI – Consultant

Role

We are looking for highly skilled Data Scientists to join our team. As a Data Scientist, you’ll design and deliver GenAI solutions (LLM/RAG) and applied ML components, taking prototypes through to production with strong evaluation, observability and governance. You will work closely with cross-functional teams, including data engineers, analysts, and business stakeholders, to turn data into actionable strategies that drive business outcomes.

Key Responsibilities

• Design and deliver GenAI solutions including LLM/RAG (retrieval strategy, embeddings, vector stores, prompt flows, grounding) for enterprise use cases.
• Evaluate and improve solution quality using offline/online metrics (quality, latency, cost) and iterate based on feedback.
• Harden solutions for production with observability/monitoring, tracing, guardrails, safety controls, and reliability practices.
• Build and integrate model endpoints into products and workflows (APIs/services), partnering with engineering through to deployment.
• Work across cloud platforms (Azure/AWS/GCP) integrating storage, compute, orchestration, and model/runtime components.
• Assess data readiness for modelling/RAG (fitness, quality, access) and define remediation requirements.
• Collaborate in cross-functional squads (DS/DE/engineering/product) and contribute to reusable assets and ways of working.
• Communicate clearly with stakeholders on trade-offs, evaluation results, risks, and adoption actions.
• Own end-to-end workstream delivery, lead stakeholder conversations, mentor others (more senior levels).
• Shape solution direction and quality bar, coach teams, contribute to sales pursuits/bids and accelerators (most senior levels).

Essential Skills

• Strong Python/R (pandas/NumPy; ML libs such as scikit-learn; DL frameworks TensorFlow/PyTorch).
• Experience with LLM/RAG toolchains (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector search (e.g., Pinecone, Weaviate, FAISS, Azure AI Search).
• Experience with GenAI platforms (e.g., OpenAI API, Anthropic, Gemini, Llama or equivalents).
• Exposure to big data/distributed computing and pipeline/feature engineering.
• LLM safety & governance (hallucination mitigation, grounded responses, audit trails).
• Degree in a quantitative field.
• Right to work in the UK without sponsorship.

Preferred Skills

• Cloud ML experience (AWS/GCP/Azure).
• Strong SQL; experience with visualisation tools (Tableau/Power BI or Python viz).
• Specialisms: NLP / computer vision / time series.
• NoSQL familiarity.
• Quant / trading analytics engineering practices.
• Time-series forecasting (prices, demand, blend outcomes, scheduling effects).
• Optimisation / simulation (planning, blending, logistics constraints).
• Model risk controls (bias/leakage checks, backtesting discipline, monitoring/drift).
• CI/CD, deployment, monitoring; Docker/Kubernetes.
• Experiment design and randomised trials.
• MSc with PhD a plus.

Personal Attributes

• Analytical, pragmatic problem-solver; outcome-oriented.
• Self-directed, able to prioritise and juggle multiple workstreams.
• Clear communicator who can simplify complexity.
• Collaborative, curious, continuous learner.

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