Senior Analyst & Data Specialist

Liverpool
9 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Senior Data Analyst - HOTH

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Analyst & Data Specialist

Location: Liverpool

Working style: Hybrid

About the Role:

In this role, the successful candidate will play a key part in supporting data projects, providing expertise in database development, data security, and documentation. Working closely with the wider data project team, you will help implement a new core platform and support the Finance Domain's reporting requirements. You will interpret raw data, transforming it into actionable insights for senior stakeholders. This role involves daily collaboration with the Data Architect, Head of Data and Analytics, and the Director of Finance, Risk, and Compliance.

Key Responsibilities:

Perform advanced data analysis on large datasets to extract actionable insights.
Identify/interpret trends, patterns and correlations to support strategic and operational decision-making.
Conduct detailed analyses across the business, producing clear, informative outputs and making recommendations that influence key business decisions.
Create clear and concise visualisation's to communicate data insights to both technical and non-technical stakeholders.
Automate reporting processes to enhance efficiency and accuracy.
Collaborate with product, marketing, finance, and operations teams to identify data-driven business opportunities.
Translate business requirements into technical specifications for data extraction and analysis.
Develop methods to ensure data integrity, accuracy, and consistency.
Establish and promote best practices for data management, storage, and security.
Work with IT and Data Engineering teams to optimise data pipelines and infrastructure.

You will need:

Experience in a senior Business Intelligence role, preferably within the finance industry.
Strong SQL skills within a reporting environment.
Proficiency with business reporting software solutions (Power BI preferred).
Detail-oriented approach, with a focus on delivering high-quality, accurate work.
Ability to manage multiple projects and work under tight deadlines when needed.

Desirable Requirements:

Experience with cloud platforms such as AWS, Google Cloud and Azure (or other similar systems)
Knowledge of data governance and compliance regulations (e.g., GDPR).

Additional Information:

The company we are partnered with will not be providing sponsorship for this role.

Inventum Group is passionate about equity, diversity and inclusion. We seek individuals from the widest talent pool and encourage underrepresented talent to apply for vacancies with us. We are committed to recruitment processes that are fair for all, regardless of background and personal characteristics. If you require any adjustments to apply for a role with us, please let us know in whatever way suits you best. Inventum Group is a Recruitment and ED&I Consultancy Business.

Inventum Group is acting as an Employment Agency in relation to this vacancy

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.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 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.