Lead Data Analyst

Harnham - Data & Analytics Recruitment
London, United Kingdom
Today
£55,000 – £65,000 pa

Salary

£55,000 – £65,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
Hybrid
Seniority
Lead
Education
Degree
Posted
30 Apr 2026 (Today)

Benefits

Hybrid working with one day per week at London Bridge Advanced analytics, modelling and measurement projects Strong progression opportunities in a growing data function

Lead Data Analyst


London Bridge hybrid, £65,000 plus benefits

A great opportunity to take on a strategic Lead Data Analyst role where you will work across experimentation, modelling and BI projects, while shaping long term data strategy and supporting complex digital marketing programmes.

The Company
They are a high growth data and performance consultancy combining analytics, data science and engineering to drive measurable, sustainable growth for well known brands. Their work spans digital marketing data, advanced measurement and predictive modelling, with strong access to client datasets and a culture centred on technical excellence.

The Role
* Lead analytical work across experimentation, causal inference and incrementality
* Build predictive models such as LTV, propensity and forecasting
* Deliver BI and reporting projects using cloud based data and dbt pipelines
* Work hands on with SQL and digital marketing data from Google and Meta
* Partner with data scientists to deploy models into advertising platforms
* Mentor analysts and contribute to technical development across the team

Your Skills And Experience


* Strong technical ability with SQL
* Experience using dbt for transformation and production data models
* Background working with digital marketing data and ad platform signals
* Exposure to BI and analytics projects using tools such as Looker or Tableau
* Understanding of experimentation, causal inference and incrementality
* Knowledge of MMM, LTV and propensity modelling
* Confident communicator who can collaborate with a range of stakeholders

What They Offer


* Up to £65,000 salary
* Hybrid working with one day per week at London Bridge
* Advanced analytics, modelling and measurement projects
* Strong progression opportunities in a growing data function

How To Apply
If this sounds like your next step, apply today to learn more.

Related Jobs

View all jobs

Lead Data Analyst

Harnham - Data & Analytics Recruitment London, United Kingdom
£55,000 – £65,000 pa Hybrid

Data Analyst - Sc cleared

CBSbutler Holdings Limited trading as CBSbutler Reading, Berkshire, United Kingdom
£80 – £83 ph

Data Lead/Manager

Adecco Worthing, West Sussex, United Kingdom
£450 – £500 pd Hybrid

Product Data Lead

Collaborate Recruitment Parkstone, Dorset, United Kingdom
£40,000 – £43,000 pa

Data Analyst/Manager

Coulter Elite Resourcing Peterborough, PE1 1XH, United Kingdom

Data and Insight Manager

Vocative Consulting Bridgwater, Somerset, United Kingdom
£60,000 – £65,000 pa

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.