Junior Applied AI & Data Scientist
Junior Applied AI & Data Scientist

Junior Applied AI & Data Scientist

Full-Time 36000 - 60000 £ / year (est.) No home office possible
TomNext

At a Glance

  • Tasks: Design and build AI models for investment analysis and automation.
  • Company: Join a fast-paced startup transforming alternative asset investment with AI.
  • Benefits: Work in a high-trust environment with rapid prototyping and real impact.
  • Other info: Collaborate closely with experienced engineers and entrepreneurs.
  • Why this job: Shape the future of finance with cutting-edge AI and blockchain technology.
  • Qualifications: BSc/MSc in a STEM field with strong Python and ML experience.

The predicted salary is between 36000 - 60000 £ per year.

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.

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.

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.

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.

Junior Applied AI & Data Scientist employer: TomNext

At TomNext, we pride ourselves on being an innovative employer at the forefront of AI and finance, offering a dynamic work culture that fosters creativity and collaboration. As a Junior Applied AI & Data Scientist, you'll have the unique opportunity to work closely with industry leaders, rapidly prototype solutions, and see your contributions make a tangible impact in a fast-paced startup environment. With a strong emphasis on employee growth and cutting-edge technology, TomNext is committed to empowering its team members to push the boundaries of what's possible in investment intelligence.
TomNext

Contact Detail:

TomNext Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Junior Applied AI & Data Scientist

✨Tip Number 1

Network like a pro! Get out there and connect with people in the AI and finance sectors. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving AI models or data science. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do before they even meet you.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Remember, they want to see how you think and approach problems!

✨Tip Number 4

Apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight how your skills align with our mission and the role. It shows initiative and enthusiasm!

We think you need these skills to ace Junior Applied AI & Data Scientist

Data Science
Machine Learning (ML)
Python Programming
PyTorch
TensorFlow
JAX
Large Language Models (LLMs)
XGBoost
Decision Trees
Deep Learning Architectures (CNNs, RL)
Data Engineering
Pandas
NumPy
Spark
Cloud Environments (GCP)
Microservice Architecture
Containerization (Docker, Kubernetes)
Agentic AI Frameworks
Model Fine-Tuning
Prompt Engineering

Some tips for your application 🫡

Show Your Passion for AI: When writing your application, let us see your genuine enthusiasm for AI and data science. Share specific projects or experiences that highlight your love for turning messy data into intelligent systems. This will help us understand why you're the perfect fit for our team!

Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter to reflect the skills and experiences mentioned in the job description. Highlight your programming skills in Python and any experience with LLMs or diverse ML models. We want to see how you can contribute to our mission!

Be Clear and Concise: Keep your application clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and experiences. Remember, we’re looking for someone who can communicate complex ideas simply and effectively.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re proactive and keen to join our team!

How to prepare for a job interview at TomNext

✨Know Your AI Stuff

Make sure you brush up on the latest AI frameworks and models, especially those mentioned in the job description like LLMs and agentic AI. Be ready to discuss your hands-on experience with Python and any relevant projects you've worked on, as this will show your practical knowledge.

✨Showcase Your Problem-Solving Skills

Prepare to talk about how you've tackled messy, real-world data in the past. Think of specific examples where you turned complex data into usable systems. This will demonstrate your ability to bridge research and engineering, which is key for this role.

✨Get Familiar with Financial Concepts

Since TomNext operates at the intersection of AI and finance, having a basic understanding of financial data and investment workflows will give you an edge. Brush up on terms related to alternative assets and be ready to discuss how AI can innovate in this space.

✨Ask Insightful Questions

Prepare thoughtful questions about the company's AI platform and its future direction. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values. Plus, it’s a great way to engage with the interviewers!

Junior Applied AI & Data Scientist
TomNext

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