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- Tasks: Drive commercial value by solving interesting data problems and deploying 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 real impact with your data skills in diverse industries and collaborate with senior stakeholders.
- Qualifications: Experience in ML delivery and strong problem-solving skills required.
- Other info: Exciting projects with excellent career growth opportunities in a dynamic environment.
The predicted salary is between 72000 - 88000 £ 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 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 London
✨Tip Number 1
Network like a pro! Reach out to connections in the private equity and data science fields. 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 want to see your impact-driven work, so make sure it’s front and centre when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you’ve translated complex data problems into clear business outcomes. We love candidates who can communicate effectively with senior stakeholders!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals who are ready to tackle interesting data problems with us.
We think you need these skills to ace Senior Data Scientist - Private Equity Consulting in 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.
Showcase Your Impact: When detailing your past experiences, focus on the impact of your work. Use metrics and examples to illustrate how your contributions have led to measurable outcomes in previous roles.
Be Clear and Concise: Keep your application clear and to the point. Avoid jargon where possible and ensure that your skills and experiences are easy to understand for senior stakeholders who may not be technical.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
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, and NLP use cases.
✨Understand the Business Impact
It's crucial to translate your technical work into commercial value. Think about how your projects have driven business outcomes in the past. Be prepared to explain how your solutions have impacted senior stakeholders and contributed to the bottom line.
✨Familiarise Yourself with the Tech Stack
Since the role involves working with Python, SQL, Databricks, and cloud platforms like AWS or GCP, 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
Interviews are a two-way street! Prepare 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.
