National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Finance Business Analyst

London
1 month ago
Applications closed

Related Jobs

View all jobs

Buissness analyst

EMEA FP&A Manager

Data Analyst, Tracking & Business Intelligence

Senior Data Analyst

Senior Quantitative Analyst

Senior Data Science Analyst

Senior Finance Business Analyst

This pivotal role is all about driving the evolution of our finance function and processes. The individual will leverage their analytical expertise and innovative mindset to identify inefficiencies and implement strategic improvements. They will work closely with cross-functional teams to integrate new technologies, enhance data management practices, and support a seamless transition to our future state.

Key responsibilities of the role include:
Collaborating with business teams to capture their business processes and identify opportunities for optimisation and automation
Developing a comprehensive view of Finance business requirements and the data needed to generate outputs, covering both regulatory and internal Management Information (MI)
Working in conjunction with other areas to deliver a cohesive experience to the business and Finance community, while ensuring their work aligns with the standards defined by the business
The efforts of the Finance Business Process Analyst will directly contribute to optimising our financial operations, ensuring compliance, and enabling us to achieve our strategic financial goals.
As part of their work, they are expected to become an expert on a range of finance processes and applications used within the organisation, as well as having a strong understanding of all other systems either providing data to or receiving data from those financial systems.
Acting as the bridge between FP&A, Finance, Actuarial, IT, and other business areas, the focus of the role is not only to gather and structure end-user requirements but to diplomatically challenge those requirements to identify genuine business needs and then develop practical solutions to satisfy those needs.
Specific tasks will require skills such as facilitation, influencing, planning, logical thinking, requirements gathering, prioritisation, initiative-taking, multi-tasking, problem analysis, solution design, documentation of processes, user training, and handover to Business As Usual (BAU). All of this must be done in combination with excellent written and oral communication skills.

Technical knowledge:
Advanced computer skills including Microsoft Office Suite (especially Excel), SharePoint, Skype for Business, and other business productivity systems.
Experienced Visio knowledge
Exposure to a variety of business application systems such as finance, data warehouses/marts, ERP, transaction/data processing, document management, workflow

Experience required:

Understanding of the end-to-end finance process including experience in supporting teams in streamlining activities
Good quality A-levels in numerate and/or analytical subjects
At least ten years solid, business or systems analysis experience within the insurance market, with experience within the Finance area
A thorough understanding of insurance as a business
A demonstrable record of the delivery of business and technology change

A distinct advantage would be:

Experience and thorough understanding of the typical applications and business processes within an insurance finance department
Part/Qualified accountant or Lean Six Sigma
Experience with change management methodologies
Lloyds market understanding

National AI Awards 2025

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.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.

Part-Time Study Routes That Lead to Data Science Jobs: Evening Courses, Bootcamps & Online Masters

Data science sits at the intersection of statistics, programming and domain expertise—unearthing insights that drive business decisions, product innovation and research breakthroughs. In the UK, organisations from fintech and healthcare to retail and public sector are investing heavily in data-driven strategies, fuelling unprecedented demand for data scientists, machine learning engineers and analytics consultants. According to recent projections, data science roles will grow by over 40% in the next five years, offering lucrative salaries and varied career paths. Yet many professionals hesitate to leave their current jobs or pause personal commitments for full-time study. The good news? A vibrant ecosystem of part-time learning routes—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn data science while working. This comprehensive guide explores every pathway: foundational CPD units and short courses, hands-on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re an analyst looking to formalise your skills, a software developer pivoting into data or a manager seeking to harness data-driven decision-making, you’ll find the right route to fit your schedule, budget and career goals.

The Ultimate Assessment-Centre Survival Guide for Data Science Jobs in the UK

Assessment centres for data science positions in the UK are designed to replicate the multifaceted challenges of real-world analytics teams. Employers combine psychometric assessments, coding tests, statistical reasoning exercises, group case studies and behavioural interviews to see how you interpret data, build models, communicate insights and collaborate under pressure. Whether you’re specialising in predictive modelling, NLP or computer vision, this guide provides a step-by-step roadmap to excel at every stage and secure your next data science role.