Graduate Data Analyst

Ocho
Belfast
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Data Engineering Coach

Graduate Business Systems Analyst

Entry Level Investment Analyst

Entry Level Investment Analyst

Entry Level Investment Analyst

Graduate / Entry-Level Data Analyst (SQL Developer) Data Visualisation & Reporting Please note: While this role is titled "Graduate," if you do not have a third-level qualification but have the relevant data background, you are still encouraged to apply. About Us My client is a leading provider of professional outsourcing services to financial organisations, including UK-based lenders and international asset management companies. They specialise in managing client portfolios, ensuring financial health and stability for millions worldwide. With a growing team of 51 employees, my client is seeking a Graduate / Entry-Level Data Analyst to join their dynamic Data Integration, Reporting & Analysis team. The Role As a Data Analyst (SQL Developer) focusing on Data Visualisation & Reporting, you will work in a fast-paced environment, delivering key data insights to both internal and external stakeholders. Your role will involve creating and maintaining dashboards, analysing performance metrics, and ensuring data accuracy. Youll play a key role in developing forecasting models and delivering actionable reports to help senior management and clients make informed decisions. Key Responsibilities Design, build, and maintain reports using SSRS, Tableau, or Power BI. Write SQL queries to extract data from complex databases. Monitor KPIs and identify key trends for senior management. Identify and resolve discrepancies or outliers in datasets. Automate and enhance existing reporting processes. Collaborate with internal and external stakeholders on various data projects. You Should Have Strong knowledge of SQL programming for databases. Experience using Tableau and/or Power BI for data visualisation. Solid understanding of T-SQL and database design concepts. Experience in building professional dashboards, graphs, and tables. Creative problem-solving skills with strong organisational abilities. A degree (or equivalent experience) in Data Analytics, Data Science, or Data Engineering. Bonus Skills Experience with R or Python for data analysis. Previous experience in financial services or working with MS SQL Server Integration Services (SSIS). Experience in automating communication and data processes. Why Join This Business? Competitive salary based on experience. Private Health Insurance and Workplace Pension. 24 days annual leave, plus 11 statutory holidays. Flexible working options, including remote work after induction. Full-time hours (37.5 per week) with flexibility for other work patterns. How to Apply To apply, please send your CV via the link below. Alternatively, if youd like more details, feel free to reach out to Ryan Quinn on LinkedIn. Benefits: Bonus Hybrid working

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.