Data Scientist - Global Investment Firm

Harnham
City of London
4 days 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–£65,000 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.

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