Data Analyst - Sales Operations

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

Related Jobs

View all jobs

Data Scientist

Randstad Technologies Recruitment London, United Kingdom

Data Scientist

Vallum Associates London, United Kingdom

Senior Forensic Data Analytics Manager

Brimstone-Recruitment Dublin, City Of Dublin, Ireland

Director: Forensic Technology/Data Analytics/FinCrime/Regulatory

Brimstone-Recruitment City Of Dublin, Ireland

SVP Delivery, EMEA

Quantexa London, United Kingdom
£150,000 – £200,000 pa Hybrid

Senior Full Stack Engineer (Must be based in UK)

PolyAI London, United Kingdom
£40,000 – £70,000 pa On-site
Posted
1 Oct 2025 (7 months ago)
Share
Save job
Create job alert

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.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning 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.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.