Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Tackle exciting data challenges and drive real business value with ML solutions.
- Company: Fast-growing AI firm in London, focused on private equity consulting.
- Benefits: Competitive salary, hybrid work model, generous holiday, and comprehensive health coverage.
- Why this job: Make a tangible impact in diverse industries while working with senior stakeholders.
- Qualifications: Experience in ML delivery and strong collaboration skills required.
- Other info: Join a dynamic team with opportunities for growth and innovation.
The predicted salary is between 72000 - 96000 £ per year.
Do you want to work on interesting data problems to drive commercial value? Have you taken models from prototype to production in messy, real-world environments? Are you ready to work with senior stakeholders in private equity portfolios?
We’re hiring for a fast-growing, London-based investment-focused AI firm that partners with private equity and investment groups to embed data science and machine learning into portfolio companies. Backed by recent investment and partnered with leading European PE firms, the business is scaling its deployment team to deliver measurable value across diverse industries.
This Senior Data Scientist / Senior Machine Learning Engineer role sits within the deployment group, working hands-on with portfolio companies post-deal to design, build, and deploy ML solutions that improve real business outcomes. Projects are varied, impact-driven, and typically delivered over 2–6 month cycles.
Key Responsibilities- Own end-to-end ML delivery from problem definition through deployment
- Build and productionise models across forecasting, pricing, churn, segmentation, fraud, and NLP use cases
- Work closely with data engineers and cloud infrastructure to scale solutions
- Translate technical work into clear commercial impact for senior stakeholders
- Contribute to code quality, deployment standards, and best practices
- Salary: £90,000–£110,000 base + 15–20% discretionary bonus
- Working model: Hybrid, 2–3 days per week in a central London office (flexible)
- Tech stack: Python, SQL, Databricks, AWS/GCP/Azure, Git, Docker
- Benefits: 7% employer pension, private medical (family cover), life assurance, income protection, 25 days holiday + bank holidays
- Visa: Sponsorship available
Interested? Please apply below.
Senior Data Scientist - Private Equity Consulting in City of London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Private Equity Consulting in City of London
✨Tip Number 1
Network like a pro! Reach out to connections in the private equity and data science space. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those that demonstrate your ability to take models from prototype to production. We love seeing real-world applications of your work, so make sure to highlight any impactful results you've achieved.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding the business side of things. Be ready to discuss how your ML solutions can drive commercial value. We want to see that you can translate complex concepts into clear benefits for senior stakeholders.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate candidates who are eager to tackle interesting data problems. Don’t miss out on the chance to join our fast-growing team!
We think you need these skills to ace Senior Data Scientist - Private Equity Consulting in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Data Scientist. Highlight your experience with ML models and any relevant projects that showcase your ability to drive commercial value.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science in private equity. Share specific examples of how you've taken models from prototype to production, and how you can contribute to our team.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python, SQL, and cloud platforms like AWS or GCP. We want to see how your technical expertise aligns with our tech stack and the projects you'll be working on.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Harnham
✨Know Your Data Science Stuff
Make sure you brush up on your data science and machine learning knowledge. Be ready to discuss specific models you've built and how you've taken them from prototype to production. Prepare examples that showcase your experience with forecasting, pricing, churn, segmentation, fraud, and NLP use cases.
✨Understand the Business Impact
It's crucial to translate your technical work into clear commercial outcomes. Think about how your projects have driven value in previous roles and be prepared to explain this to senior stakeholders. They want to see how your work can impact their bottom line.
✨Familiarise Yourself with the Tech Stack
Since the role involves working with Python, SQL, Databricks, and cloud platforms like AWS, GCP, or Azure, make sure you're comfortable discussing these technologies. If you have experience with Git and Docker, highlight that too, as it shows you're ready for a collaborative environment.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s approach to data science and how they measure success. This not only shows your interest but also helps you gauge if the company aligns with your career goals. Plus, it gives you a chance to engage with your interviewers on a deeper level.
