Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build AI and data science solutions that influence high-value business decisions.
- Company: Global investment firm at the forefront of technology and data.
- Benefits: Competitive salary, bonus, and a flexible 4-day work week.
- Why this job: Gain real ownership and impact in a fast-paced, innovative environment.
- Qualifications: 2+ years of data science experience and strong Python skills.
- Other info: Collaborate with engineers and stakeholders on diverse projects.
The predicted salary is between 42000 - 58000 £ per year.
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 summaryYou 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
- 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.
Data Scientist - Global Investment Firm in City of London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Global Investment Firm in City of London
✨Tip Number 1
Network like a pro! Reach out to current employees at the firm on LinkedIn. Ask them about their experiences and any tips they might have for your application. It’s all about making connections that can help us stand out!
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Make sure you can talk confidently about your past projects, especially those involving Python and data science. We want to show them we’re ready to hit the ground running!
✨Tip Number 3
Don’t forget to showcase your problem-solving skills! Be ready to discuss how you’ve tackled challenges in previous roles. This is key for a Data Scientist role where decision-making is crucial.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team. Let’s make it happen!
We think you need these skills to ace Data Scientist - Global Investment Firm in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Scientist role. Highlight your experience with Python, data science foundations, and any relevant projects you've worked on that showcase your ability to take models from exploration to production.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Mention specific examples of your work in AI and data science solutions that have influenced business decisions, as this will resonate with what we're looking for.
Showcase Your Projects: If you've worked on interesting data science or NLP/LLM projects, make sure to include them in your application. We love seeing real-world applications of your skills, so don't hold back on sharing your achievements and the impact they had.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people in our team.
How to prepare for a job interview at Harnham
✨Know Your Data Science Fundamentals
Brush up on your classical data science foundations. Be ready to discuss your experience with models, especially how you've taken them from exploration to production. This firm values hands-on experience, so be prepared to share specific examples of your work.
✨Showcase Your Python Skills
Since the role requires solid Python engineering, make sure you can demonstrate your coding abilities. Bring along a portfolio or examples of your previous projects that highlight your proficiency in Python and any relevant libraries you've used.
✨Understand the Business Context
This is a global investment firm, so it's crucial to understand how data science influences business decisions. Research their operations and think about how your skills can support commercial decision-making. Be ready to discuss how your work can add value to their processes.
✨Prepare for Technical Communication
You'll need to collaborate closely with both technical and non-technical stakeholders. Practice explaining complex concepts in simple terms. Think of examples where you've successfully communicated technical information to non-technical audiences, as this will show your ability to bridge the gap.
