Senior Reporting Analyst

Queens Park
4 weeks ago
Create job alert

Senior Reporting Analyst

  • Salary: The starting salary is £47,060, which includes allowances totalling £2,928.
  • The salary is broken down as £44,132 basic salary, which will increase annually until you reach the top of the scale £52,652 Plus, a location allowance of £1,928 and a non-pensionable allowance of £1,000.
  • Location: Kilburn
    We’re currently setting up Met Business Services (MBS) which will streamline our Commercial, Finance and HR services. MBS will be a highly focused front-line organisation, reducing admin and providing easy to use interfaces and ‘one-touch’ services for end-users that leverage the potential of contemporary technologies.
    A key part of MBS will be the Data and Solutions Capability, and we’re currently looking for a Senior Reporting Analyst to drive and maintain reporting services that enable data-driven decision-making and compliance. This role will involve collaborating with cross-functional teams to establish best practices, supporting users with training, and enhancing data capability across the Met. The ideal candidate will be analytically minded and eager to learn the new reporting platform that’s essential to MBS’s operations.
    As Data Analyst you’ll have a number of core duties relating to MBS reporting. These include:
  • Leading the design and build of visually compelling dashboards and reports to drive business insights
  • Gathering reporting requirements and defining the KPIs, measures and metrics for reporting solutions, and storing this critical data centrally
  • Analysing data within reports to provide pertinent insights that inform stakeholders’ strategic decision-making
  • Leading all reporting and dashboard testing and ensuring a high level of quality assurance is met before reports and dashboards are published
  • Owning the creation of the technical documentation required to support the team
    How to apply
    Click the apply now button below and start your career at the Met. Applications will be via a detailed CV, Personal Statement, and online application form. Your personal statement should outline why you are interested in the role and how your skills and experience demonstrate your suitability for the role. (NB. Please do not attach 2 copies of your CV).
    Once received, your Data Analyst application will be reviewed against eligibility criteria, following this, your application will be reviewed by the hiring manager. The application review for this vacancy will commence 1 week after the vacancy has closed.
    Following Data Analyst application review, successful Data Analyst candidates will be invited to interview. Interview dates will commence 1 week after the hiring managers review.
    The Met is committed to being an equitable (fair and impartial) and inclusive employer for disabled people, striving to have a diverse and representative workforce at all levels. We encourage applications from people from the widest possible range of backgrounds, cultures and experiences. We particularly welcome applications from people with disabilities and long-term conditions, ethnic minority groups, and women.
    As a Disability Confident employer, the Met has committed to making disability equality part of our everyday practice. We ensure that people with disabilities and those with long term conditions have the opportunities to fulfil their potential and realise their aspirations.
    The Met is committed to making reasonable adjustments to the recruitment process to ensure disabled applicants can perform at their best. If you need any reasonable adjustments or changes to the application and recruitment process, we ask that you include this information within your application form. All matters will be treated in strict confidence.
    Data Analyst, Reporting Analyst

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Business Intelligence and Reporting Analyst

Credit Risk Analyst

Senior Data Analyst

Senior Business Analyst - Surrey - £65k

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.