Data Scientist - Global Investment Firm

Harnham
London
1 week ago
Create job alert

Do you want to build AI and data science solutions that directly influence high-value business decisions?

Have you taken models from exploration through to production in real environments?

Are you ready to work in a small, high-impact team with real ownership and autonomy?


This organisation is a global investment firm operating at the intersection of technology, data, and decision-making. They have built an internal data and technology function to support deal sourcing, due diligence, and portfolio insights, using modern data science and emerging LLM/NLP techniques. The team works closely with senior stakeholders and operates like a lean product and research group within a fast-paced commercial environment.


They are hiring a Data Scientist (2+ years of experience) to join their London team. This role offers exposure across research, production deployment, and short-form analytical projects, with genuine end-to-end ownership rather than narrow modelling work.


Role summary

You will work as a generalist Data Scientist, combining strong classical data science foundations with solid Python engineering and familiarity with modern ML/LLM tooling. The role is hands-on and delivery-focused, with opportunities to ship work into production and iterate quickly.


Key responsibilities

  • Build and prototype data science and NLP/LLM solutions
  • Take models from exploration to production deployment
  • Work across multiple projects supporting commercial decision-making
  • Collaborate closely with engineers and non-technical stakeholders
  • Maintain high coding standards and clear technical communication


Key details

  • Salary: £60,000–£70,000 base + 10% bonus
  • Location: Central London (Bond Street)
  • Working model: 4 days per week in the office (Mon–Thu)
  • Tech stack: Python, classical DS, cloud (GCP preferred; AWS/Azure acceptable), LLM/NLP tooling
  • Visa sponsorship: Not available


Interested? Please apply below.

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.