Data Scientist

Farringdon, Greater London
2 hours ago
Create job alert

Data Scientist

Salary: £85,000 - £95,000 + Equity
Location: London (Hybrid - 2-3 days per week in office)

We are currently looking for a Data Scientist to join a fast-paced, early-stage AI startup building cutting-edge technology in the mobile app space. Reporting directly into the CTO, this Lead Data Scientist will play a critical role in shaping the company's core product and driving real commercial impact from day one.

As a Data Scientist, you'll be working at the heart of the business, designing and deploying machine learning models that predict user behaviour, helping clients optimise for revenue, retention, and long-term value rather than just installs. This Lead Data Scientist will take ownership of a key part of the platform, working closely with the founders to turn complex data into actionable, high-impact solutions.

Day-to-day, the Data Scientist will be building models, experimenting with new approaches, and continuously improving performance across customer datasets. You'll be operating in a highly collaborative but autonomous environment where your work directly influences product direction and business outcomes.

The Opportunity

This is a genuinely high-impact role, where you'll have ownership, visibility, and the chance to shape both the product and the company's future.

As a Data Scientist, you will:

Design and build advanced machine learning models focused on:
User behaviour prediction
Churn and propensity modelling
Develop a scalable "model factory" capable of generating bespoke models per client
Work with complex behavioural event data from mobile applications
Collaborate directly with the founders on product and technical direction
Continuously experiment, iterate and improve model performance
Own a key part of the data science stack end-to-endWhat makes this different?

You're not optimising dashboards, you're building the core product
Your work directly impacts client revenue and acquisition strategy
You'll operate with real ownership, not layers of process
It's a chance to join early and help shape a product with a clear path to exit

What's in it for you?

£85,000 - £95,000 base salary
Meaningful equity in a high-growth startup
Opportunity to work alongside experienced founders
High ownership and autonomy from day one
Exposure to cutting-edge machine learning challenges
Clear progression as the company scales
Hybrid working (London-based, 2-3 days in office)

Skills and Experience

Must have:

Strong experience in machine learning / data science (typically 4-8+ years)
Proven experience building and deploying ML models in production
Solid understanding of:
Churn modelling
Propensity modelling
Behavioural data analysis
Strong Python skills (e.g. Pandas, NumPy, ML libraries)
Experience working with real-world, messy datasets
Ability to work autonomously in a fast-paced environment

Nice to have:

Experience in mobile apps, subscription products or growth analytics
Exposure to experimentation / A/B testing environments
Experience working in early-stage startups
Familiarity with building scalable ML systems or pipelines
Commercial mindset - understanding how models impact revenueIf you would like to be considered for the role and feel you would be an ideal fit with the team, please send your CV by clicking on the Apply button below

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - SC Cleared

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.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

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.