Data Analyst

iO Associates - UK/EU
Leicestershire
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Location:Leicestershire
Salary:Up to £46,000 + Bonus & Benefits
Working Pattern:3 days a week after onsite probation

About the Role

We are looking for a Data Analyst to join a dynamic and growing team within a well-established organisation. This is an exciting opportunity for someone who enjoys working with large datasets, automating processes, and delivering high-quality reporting solutions using modern tools and technologies.

In this role, you will support key business functions, ensuring the accuracy, integrity, and efficiency of data reporting. If you are a problem-solver with a passion for data and process improvement, this could be the perfect role for you.

Key Responsibilities

  • Design and maintain robust data pipelines and models to enhance reporting processes.
  • Ensure consistency, accuracy, and completeness in business data reporting.
  • Streamline reporting workflows, integrating failure checks and monitoring solutions.
  • Take ownership of issues and drive timely resolutions.
  • Work closely with internal teams, providing meaningful insights to support key business decisions.
  • Identify and implement enhancements to optimise data analysis and reporting.

What We're Looking For

  • Proficient in SQL (T-SQL / S-SQL).
  • Strong skills in Excel, including Power Pivot and Power Query, with the ability to handle complex datasets.
  • Ability to interpret business data and provide clear, concise insights.
  • Two to five years of experience in a large organisation, ideally within a commercial or corporate environment.
  • Confident working with both technical and non-technical stakeholders.
  • A collaborative approach and ability to work effectively within a team.

Desirable Skills

  • Experience with Power BI for data visualisation, including DAX, M language, or Power Query.
  • Familiarity with Azure Data Lakes and its application in data analytics.
  • Experience working on Data Bricks
  • Knowledge of SSRS reporting tools.
  • A willingness to learn or experience with statistical languages such as Python or R.

This is an opportunity to be part of a leading organisation that values innovation and professional growth. You will work in a fast-paced environment where your contributions will have a real impact on business performance. Alongside acompetitive salary of up to £46,000, you will benefit from a generous bonus scheme, excellent career progression opportunities, and a supportive team culture.

Apply today to take the next step in your data career.

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.

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.

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.

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.