Data Analyst - Sales Operations

EF Recruitment
Victoria, Greater London, SW1P 1BX, United Kingdom
7 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Healix Esher, United Kingdom

Data Analyst

Jackson Hogg Newton Aycliffe, United Kingdom

Data Analyst

Adria Solutions Derbyshire, United Kingdom
£40,000 – £50,000 pa

Data Analyst

ARM City of London, United Kingdom

Data Analyst

Carbon 60 United Kingdom

Data Analyst

Travail Employment Group Wellingborough, NN8 1AF, United Kingdom
Posted
30 Sep 2025 (7 months ago)

Our client is a global SaaS type company who are now seeking a Sales Operations Data Analyst based at their impressive UK headquarters in central London. This is a 3-6 month contract, hybrid, with 3 days a week in the office.

You will be supporting their EMEA business working directly with their sales and marketing teams.

Duties

* Design and build interactive and intuitive Customer Success dashboards to report on retention and revenue generating activities.

* Utilize SQL and Python to query databases, perform data manipulation, and automate analysis processes.

* Support experimentation on Growth & Retention success by analyzing and reporting on A/B testing.

* Present findings and insights to business stakeholders and executives in a clear and concise manner.

Skills

* High proficiency in SQL, Excel.

* Proven experience in building dashboards in Tableau and Qliksense (or similar reporting tools).

* Experience with A/B testing methodologies and analysis.

* 3+ years of relevant experience working with web and call centre data.

* Ability to manage time effectively and prioritize tasks to meet project deadlines.

Benefits

* Friendly supportive team

* Informal dress code

* Global organisation.

* Hybrid role

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.