Data Scientist

Data Scientist Help build the AI and data platform changing how financial advice is delivered. Reporting to - Chief AI OfficerEmployment - Full timeLocation - Remote within the UK, with travel for team and customer meetings when required About AfternoonAfternoon is building the operating system for modern financial advice firms. We are replacing fragmented systems and manual processes with one AI- and data-first platform that helps firms work faster, deliver better advice and serve more clients.At the heart of Afternoon is a genuinely difficult technical problem. We connect investment data from 27 platforms with client records, documents, meetings and communications, then use AI to turn that information into dependable, source-attributed outputs. Firms can prepare for meetings, capture and structure conversations, maintain client records, create complex advice reports and communicate with clients in one connected system.Our growth over the past year has been strong. We are working with a rapidly growing number of advice firms, have a live B2B partnership with a UK bank and are increasingly being recognised across the market. Afternoon won the lang cat's Advicetech Catwalk 2026, voted for by more than 150 advisers, and was named Professional Services Start-up of the Year for Scotland at the UK StartUp Awards. We were also selected for J.P. Morgan's Fintech Forward 2026 programme.We are well capitalised, ambitious and entering an important stage of growth. The team is still small enough for every new hire to shape the product, technical direction and company we become, while solving problems that matter to a large and established industry. The opportunityThis is an opportunity to join Afternoon at the point where the product is proven, momentum is building and there is still enormous scope to shape our approach to AI. We are looking for a production-focused data scientist to help Afternoon understand and use information held across documents, conversations, client records and investment platforms. You will work on applied NLP and machine-learning problems where accuracy, evaluation, provenance and usability matter as much as model capability.This is not a research-only role and it is not about producing isolated proofs of concept. You will take problems from exploration and experimentation through to production, working closely with software engineers, product colleagues and financial-advice specialists. You will see customers use what you build and help establish the data-science foundations for the next stage of our growth. The role suits someone who enjoys messy real-world data, asks good questions and wants to build systems that users can rely on. What you will do

• Develop and deploy NLP and machine-learning systems for extraction, classification, retrieval, summarisation and structured generation.
• Work with LLMs, smaller task-specific models and deterministic methods, choosing the right approach for each problem rather than defaulting to one model or provider.
• Build systems that extract structured, source-attributed information from complex financial documents and unstructured text.
• Design evaluation frameworks, datasets and metrics that measure quality, identify failure modes and support safe iteration.
• Create and maintain data and ML pipelines covering preparation, experimentation, training or fine-tuning, inference and monitoring.
• Work confidently with customers to understand their needs, translate them into clear technical problems and help bridge the gap between customer requirements and product development.
• Collaborate with engineers to expose models through reliable APIs and integrate them into production product workflows.
• Investigate customer and product problems directly, turn them into testable technical hypotheses and communicate findings clearly.
• Improve reproducibility, experiment tracking, documentation and standards across the data-science lifecycle.
• Monitor performance in production and use evidence and user feedback to improve models and workflows over time.

What we are looking for

• Strong Python skills and experience writing clear, maintainable production code.
• Practical experience developing and deploying NLP or machine-learning systems, including some combination of transformers, classifiers, LLMs, named-entity recognition, embeddings and retrieval.Strong initiative and the confidence to work independently, make progress and bring people in when their input is needed
• Experience working with the Hugging Face ecosystem or comparable modern ML tooling.
• A strong grasp of evaluation, experimental design and the trade-offs between model quality, latency, cost and maintainability.
• Experience creating data or ML pipelines and moving work beyond notebooks into production services.
• The ability to explain technical decisions, limitations and results clearly to engineers, product colleagues and domain experts.
• Curiosity, ownership and comfort working through ambiguity in a small, fast-moving team.

Useful additional experienceYou do not need to have all of these, but any of the following would be valuable:

• Structured data extraction using OCR, layout-aware models or vision-language models.
• Fine-tuning techniques such as SFT or LoRA, with a clear understanding of when fine-tuning is worthwhile.
• Synthetic-data generation, weak supervision or self-supervised approaches where labelled data is limited.
• Structured generation, function calling, tool use or agentic workflows.
• FastAPI, Pydantic and the deployment of Python services.
• Experiment-tracking and observability tools such as MLflow, ZenML or Opik.
• Financial services, regulated products or other domains where traceability and human oversight are essential.

What we offer

• 25 days of annual leave, plus UK bank holidays.
• A remote-first working environment, with regular opportunities to work together in person.
• Significant ownership and the opportunity to shape the product, technical approach and ways of working.
• Direct access to experienced company and technical leaders, with scope to grow as Afternoon grows.
• A benefits package that will continue to develop with input from the team.

How to applyPlease send your CV and a short note explaining what interests you about Afternoon and the problems you would like to help us solve. We welcome candidates whose experience does not match every point but who can demonstrate strong judgement, learning ability and relevant impact.