National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Analyst - Flexcube

Payments Recruitment Limited
Newcastle upon Tyne
2 weeks ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

(Flexible Interim) Data Analyst – Flexcube


· Rate - € / £ Negotiable

· Location – fully remote, UK or Europe


We are looking for an experienced Data Analyst to join our client, a global financial technology scale-up, with a focus on payment processing. We need you to join us, reporting to our CTO, and design/deliver impactful reporting and analytical solutions. You'll play a pivotal role in transforming complex system data into clear, actionable intelligence, empowering our business with reporting tools and integrated insights.


If you have experience in Oracle, Flexcube, PowerBI, dashboarding data on Flexcube & experience working for a bank or financial institution, please reach out!


Main Responsibilities:

  • Collaborate with key stakeholders to bring analytical thinking and problem-solving to the table—helping improve how we report, analyse, and use data to drive better business decisions and measurable performance improvements.
  • Act as the bridge between data preparation and analysis.
  • Get involved in automating reporting processes to boost efficiency, accuracy, and overall quality.
  • Make sure stakeholders receive accurate, timely reports they can rely on.
  • Support the rollout of our Data and Analytics strategy, and play your part in shaping and delivering the wider strategy—on time, on budget, and to spec.
  • Continuously develop and refine data and reporting processes so we can consistently provide the right insights to senior leadership.


About you:

  • Strong understanding of data analytics, business intelligence, and reporting tools, with a focus on: Oracle Flexcube, PowerBI, dashboarding data on Flexcube & experience working for a bank or financial institution.
  • Ability to quickly learn and apply knowledge beyond your core expertise.
  • Excellent analytical and problem-solving skills.
  • Proven ability to communicate complex data concepts clearly to non-technical stakeholders.
  • Proficiency with BI tools such as Power BI and other platforms used for delivering business insights.
  • Relevant experience in data analysis, business intelligence, or a related discipline.
  • Practical experience with data visualization and reporting tools to effectively present information.
National AI Awards 2025

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.

Jobs

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Education

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

Careers

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.

🍪 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.