TomNext on cord

TomNext

Junior Applied AI & Data Scientist

External position
London, UK
FinTech · Data · Machine Learning and AI
The intelligence layer for private markets
The company is no longer hiring for this position.

Skills & Experience

Job roles: AI Engineer, Data Scientist
Experience level: Junior
Tech stack/tooling used: Python, PyTorch, Tensorflow, LLMs (Large Language Models), Pandas, Numpy, Spark, FastAPI, Flask, GCP
Core skills considered: Python, PyTorch, Tensorflow, LLMs (Large Language Models), Pandas
Other skills considered: Numpy, Spark, FastAPI, Flask, GCP

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid (up to 3 remote days p/w)
Visa sponsorship: Not available

Job Description

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.

Interview Process

TBC

Skills of candidates in conversation

Python
Machine Learning
SQL
PyTorch
Pandas
S
Co-founder & CCO
Active 6 months ago
TomNext are no longer hiring for this position.

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
Alex Yeates on cord
Message Alex Yeates at Starling Bank
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