BI Reporting Analyst

Oxford
2 months ago
Applications closed

Related Jobs

View all jobs

BI and Reporting Analyst

Investment Banking Controls BA/Data Analyst Belfast £600/day

BI/MI Manager

Data & Insights Analyst

Commercial Insights Manager - Data Analyst

HR Business Intelligence Analyst

Job Title: BI Reporting Analyst
Salary: £40,000 - £45,000 base salary depending in experience
Location: Oxford / Hybrid working
Why this job 'does good'

  • Empower decision-makers: Provide the critical data insights that inform better business choices..
  • Enhance data excellence: Create well-structured reporting systems that improve the quality and accessibility of information.
  • Foster a data-driven culture: Help establish an environment where data analysis is a primary tool for success.
    Role Responsibilities and Main Duties
  • BI Report Development: Design and implement robust business intelligence reports and dashboards using leading BI tools (Power BI, Tableau, Qlik, etc.)
  • Collaboration: Work directly with teams across the organisation to understand their data needs and create solutions that drive action.
  • BI Lifecycle Management: Oversee the end-to-end process of BI reporting, from gathering needs to final deployment.
  • Data Analysis: Analyse data to uncover trends, insights, and potential areas for improvement.
  • Data Integrity: Maintain high standards of accuracy and consistency across all reports.
  • User Training and Support: Empower colleagues to maximise their use of BI tools and gain an in-depth understanding of data results.
  • Performance Optimisation: Proactively monitor and improve BI reporting performance.
  • Strategic Improvement: Identify areas to streamline processes and enhance overall efficiency through the effective use of technology.
  • Data Culture Champion: Instill a data-driven mindset across the organisation, encouraging continuous learning and better decision-making.
    Who We Are Looking For
    Essential
  • Proven Experience: Good experience in BI reporting or a data analysis role.
  • Technical Expertise: Mastery of BI tools like Power BI, Tableau, or Qlik.
  • Analytical Mind: Ability to interpret data and extract clear, actionable business insights.
  • Data Understanding: Solid grasp of data warehousing and ETL processes.
  • Communication Skills: Can explain complex data concepts to both technical and non-technical audiences.
    Desirable
  • Database Savvy: Experience with SQL and database technologies.
  • Data Governance: Knowledge of data modeling and best practices in data governance.
  • Big Data Knowledge: Understanding of big data technologies (Hadoop, Spark, etc.)
  • Advanced Analysis: Experience with advanced statistical methods

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.

Jobs

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.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 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.