We are working with a well-established financial services organisation undergoing significant investment in its data and AI capabilities.
They are looking for a hands-onData Scientist to help drive the development and deployment of GenAI solutions across the business. This role is focused on practical application – building and scaling real-world use cases.
You will work on a variety of projects, including intelligent automation, document processing, internal copilots, and customer-facing AI tools, leveraging large language models and modern machine learning techniques.
While the organisation operates in a regulated environment, they are open to candidates from a range of industry backgrounds – financial services experience is beneficial but not essential.
Key Responsibilities
- Design, build, and deploy Generative AI solutions using large language models (LLMs)
- Develop and optimise prompt engineering strategies for production use cases
- Build end-to-end pipelines (RAG, embeddings, vector search) for scalable GenAI applications
- Work with both structured and unstructured datasets, including text-heavy data
- Collaborate closely with data engineering and software teams to productionise solutions
- Identify high-impact use cases and contribute to the broader AI roadmap
- Ensure solutions align with governance, risk, and compliance standards
- Communicate insights clearly to both technical and non-technical stakeholders
Required Skills & Experience
- 3+ years’ experience in Data Science / Machine Learning roles
- Strong Python and SQL skills with hands-on experience building models and data pipelines
- Proven experience working with Generative AI (LLMs, prompt engineering, embeddings)
- Experience using frameworks such as LangChain, LlamaIndex, or similar
- Experience integrating with model APIs (e.g. OpenAI or open-source alternatives)
- Exposure to cloud environments (AWS, GCP or Azure)
- Strong problem-solving skills with a pragmatic, delivery-focused mindset
- Ability to work in cross-functional teams within a fast-paced environment
Nice to Have
- Experience within financial services or other regulated industries
- Exposure to vector databases (e.g. Pinecone, Weaviate, FAISS)
- Experience with MLOps / LLMOps and deploying models into production
- Familiarity with LLM fine-tuning, evaluation, or guardrailing techniques
- Experience building internal tools such as copilots or knowledge assistants
What’s on Offer
- Salary up to £85,000 depending on experience
- Generous benefits package
- Hybrid working (London-based)
- Opportunity to join a well-established business investing heavily in AI
- High-impact role with real ownership and visibility
- Collaborative and forward-thinking data team
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