In short

TomNext is building the AI platform that will redefine how investors access, analyse, execute, and manage alternative assets such as Private Equity and Private Credit.

Having secured funding from leading investors, including multi-family offices, fintech founders, blockchain leaders and senior figures in wealth management, we’re now looking for an Applied AI & Data Scientist to help scale a category-defining product.

Are you ready to join a fast-paced, high-trust startup at the intersection of AI and finance? Do you want to work with state-of-the-art models, build production-grade AI systems, and push the boundaries of how intelligence is applied to investing?

About TomNext

We’re transforming how people invest in alternative assets, a $13 trillion industry that has remained largely untouched by innovation. Our platform uses AI, LLMs and agentic workflows to streamline and automate complex due diligence and investment processes, empowering investors with modern tools for a legacy industry.

Who we’re looking for

We’re seeking an Applied AI & Data Scientist who thrives in a hands-on, experimental environment. You’ll help design, build and deploy AI models that form the backbone of TomNext’s investment intelligence platform, from data processing and model training to inference and automation workflows.

If you’re someone who:

• Builds fast, iterates relentlessly, and learns even faster
• Enjoys turning messy, real-world data into intelligent, usable systems
• Bridges research and engineering, comfortable both reading papers and shipping production code
• Has a genuine passion for AI frameworks, LLMs, and the next wave of intelligent automation

This is your opportunity to help shape the AI foundation of a transformational company at the intersection of finance and technology.

What you’ll do

• Design, prototype and optimize agentic AI tools that power TomNext’s investment analysis and automation.
• Integrate and structure diverse data sources to enrich TomNext’s AI-driven investment intelligence platform.
• Contribute to the operational AI stack, including data pipelines, model evaluation and deployment.
• Build and refine production-grade AI solutions using LLM APIs, RAG, MCP and Knowledge Graph technologies.
• Collaborate closely with the CTO, data engineers and product team to translate complex investment workflows into intuitive, intelligent systems.
• Research and experiment with emerging architectures, fine-tuning methods, and multimodal models to keep TomNext at the frontier of applied AI.

Must haves

• BSc/MSc (2:1 or above) in Data Science, Computer Science, Statistics, Mathematics, or a related STEM field from a UK university (or global equivalent), with demonstrated applied Data Science/ML experience (e.g., dissertation, industrial placement, internship, or competition project).
• Strong programming skills in Python, including experience with frameworks like PyTorch, TensorFlow or JAX.
• Experience working with LLMs for applied tasks.
• Practical experience with diverse ML models beyond LLMs, such as XGBoost, Decision Trees, and DL architectures like CNNs and RL.
• Familiarity with vector databases (e.g. Pinecone, FAISS, Qdrant) and RAG  pipelines.
• Proficiency in data engineering and preprocessing using Pandas, NumPy or Spark.
• Experience deploying ML models or AI agents into production (e.g. via FastAPI, Flask or Vertex AI).
• Solid understanding of cloud environments (GCP preferred), microservice architecture and containerized deployment (Docker, Kubernetes).
• Curiosity and initiative, you prototype, test, and push code without waiting for instruction.
• Has the legal right to work in the UK; visa sponsorship is not available for this role.

Nice to haves

• Exposure to agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph) or emerging standards such as Model Context Protocol (MCP).
• Experience or coursework involving LLM fine-tuning, prompt engineering, or model evaluation.
• Familiarity with transformer architectures, embeddings, or instruction-tuning concepts.
• Understanding of financial data, investment workflows, or fintech systems.
• Exposure to blockchain data, tokenisation frameworks, or on-chain analytics.
• Contributions to or interest in open-source ML or AI research projects.

Why join us

• Shape the future of how the world invests in alternative assets through cutting-edge AI, automation and blockchain innovation.
• Work side by side with the CTO and founding team, learning directly from experienced engineers and entrepreneurs building at the frontier of AI in finance.
• See your work go live fast, operate in a high-trust, high-impact startup where prototypes become production systems in weeks, not quarters.
• Experiment with frontier tools and real data, contribute to research, and grow your technical depth in a company that values creativity, precision, and execution.
• Join a mission-driven, well-funded startup backed by top investors, fintech founders, and senior figures in global financial services.