Staff Data Scientist

Harnham
City of London
12 hours ago
Create job alert

Staff Data Scientist

London, Hybrid

Salary up to £110,00 plus benefits


This is an opportunity to take ownership of marketing measurement at scale, building advanced analytics that shape how a high‑growth consumer business invests, learns and optimises. You will have real influence, working directly with senior leaders to define strategy and deliver meaningful commercial impact.


The Company

They are a well‑established, product‑led consumer marketplace with a large, engaged user base. Operating in a mobile‑first environment, they place data at the centre of decision making and continue to invest heavily in Marketing Analytics to support ambitious growth plans. They are building out their measurement capabilities and offer the chance to own complex analytical programmes across attribution, incrementality and customer value.


The Role

• Lead the development of marketing measurement frameworks across paid channels, including attribution, incrementality testing and customer value modelling.

• Build and productionise analytical models in Python or R to support performance optimisation and strategic planning.

• Partner with senior marketing stakeholders to guide investment decisions through clear, data‑driven insight.

• Collaborate with analytics, data engineering and AdTech teams to ensure accurate tracking, robust data foundations and consistent measurement approaches.

• Support BAU reporting and performance monitoring through BI tools, ensuring teams understand key drivers and outcomes.


Your Skills and Experience

• Strong commercial experience in Marketing Analytics within a digital or mobile‑first environment.

• Expertise across paid media channels and the data they generate, including platforms such as Google, Meta and TikTok.

• Hands‑on proficiency with SQL and Python or R, including building models for attribution, LTV and testing methodologies.

• Experience working with mobile measurement partners (such as Branch, Appsflyer or Kochava).

• Strong communication skills and the ability to simplify complex analysis for non‑technical audiences.


HOW TO APPLY:

Apply by sending your CV to Joe by the link below

Related Jobs

View all jobs

Staff Data Scientist

Staff Data Scientist – Experimentation: Innovation & Research

Staff Data Scientist

Staff Data Scientist – Experimentation: Innovation & Research United Kingdom, London

Staff Data Scientist

Staff Data Scientist

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.

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.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.