Business Data Analyst

Futura Design
Lutterworth, United Kingdom
Last month
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

Senior Analytics Engineer

Synthesia London, United Kingdom
Remote

SVP Delivery, EMEA

Quantexa London, United Kingdom
£150,000 – £200,000 pa Hybrid
Posted
21 Mar 2026 (Last month)
Share
Save job
Create job alert

Our motorcycle client based in Bruntingthorpe, Lutterworth is searching for a Business Data Analyst on an Inside IR35, 12-month contract working 37.5 hours a week. The successful professional can be either based in the Leicester or London office where the opportunity provides a hybrid working pattern of 1-2 days onsite, 3-4 days working from home.

Umbrella Pay Rate: £30.64 per hour.

Job Purpose:

Own the end-to-end lead journey through API integrations, data analysis, and cross-functional collaboration to drive scalable lead acquisition, qualification, and conversion. Deliver actionable insights, structured reporting, and optimisation strategies that boost lead velocity, minimise leakage, and maximise ROI across rentals, Reown, and partner ecosystems

Key Responsibilities:

Lead Journey & API Integration: Own end-to-end flow- from capture to booking- through robust API integrations, ensuring accurate lead attribution, minimal leakage, faster hand-offs, and improved online booking conversion rates.

Data Analysis & Lead Insights: Leverage a strong understanding of dashboards to track lead quality, source effectiveness and drop-offs and conversion trends, translating insights into actions that improve lead velocity and ROI.

Lead Acquisition & Nurture Strategy: Drive strategies focused on scalable lead generation, qualification and tracking, flow of leads across various stakeholders, optimisations requirement, stakeholder management between teams and nurturing at various stages.

Reporting & Governance: Deliver regular, structured reporting on lead flow, SLA adherence, enabling refinement across various stakeholders and lead management tactics.

Cross-Functional Collaboration: Collaborate closely with stakeholders like Zapier, Bemycar, MSD to maintain accuracy, efficiencies, lead flow, leakages and identify roadmaps for further improvement.

Essential Experience Required:

Minimum 3-5 years of experience in data science, API integrations, and performance management.

Experience in API integrations and Lead Flow Optimisations.

Proven experience in working with data analytics tools, statistical modelling, and data visualization.

Experience in cross functional collaboration.

Familiarity with how to use Microsoft Dynamics at an expert level.

Essential Education Required:

Bachelor's degree in a relevant field such as Data Science, Statistics, Computer Science, Mathematics, Marketing, or related field.

Postgraduate degree/diploma in Data Science, Analytics, or Digital Marketing or related field is desirable.

Preferred Experience Requested:

Media Understanding of platforms, dashboard driven decision making.

Sound understanding and appreciation of the media landscape and trends.

Experience in integrating lead sources via APIs with CRM and booking system.

Knowledge of the latest tools & innovative research methodologies.

Experience building and using unified dashboards for lead and performance monitoring.

Preferred Education Requested:

Masters in Business Administration (MBA) / Post Graduate Diploma in Management (PGDM) - Communication, Advertising, Marketing.

Certification / Licence / Professional Membership Requested:

Certification in data science, analytics, or related field (e.g., Certified Data Scientist, Certified Analytics Professional) is desirable.

Experience with data visualization tools like Tableau, Power BI, is a plus

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.