Systems Accounting Manager

Cramond Bridge
11 months ago
Applications closed

Related Jobs

View all jobs

Data Warehouse Developer

Mid-Level Data Engineer

Junior Data Analyst

Systems and Data Analyst

Senior Systems and Data Analyst (Grade L)

Data Engineer

Join us as a Systems Accounting Manager

Join a team responsible for analysis and design solutions for a wide range of finance systems, operational accounting and processes and have end to end ownership for systems accounting and operational accounting models for Finance

You’ll support the organisation in the delivery of end-to-end financial control activity

We’re looking for someone to take on a new challenge, and put their analytical and problem-solving skills to good use

What you'll do

As Systems Accounting Manager, you’ll be accountable for the delivery and integrity of monthly, quarterly and annual financial information, including balance sheet, profit and loss account, and internal and external reporting. You'll also represent Finance on core strategic bank programmes.

Along with this, you’ll act as a key partner as you proactively contribute to decision making on complex or specialist issues, demonstrating judgement and a thorough understanding of the business.

Day to day, you’ll:

Act as an internal customer relationship manager and effectively maintain relationships with stakeholders

Complete value-added reporting and analysis to meet our customers’ needs

Work with the team and centres of excellence to standardise processes and outputs and to undertake continuous improvement activity

Use in-depth technical knowledge of transaction and product systems to support the development and design of robust, fit for purpose accounting solutions

Manage and deliver data and system solutions change executed within the appropriate governance framework to maintain data integrity and data quality standards throughout the change process

Explore and recommend architectural, process and operational accounting options whilst understanding the macro change environment

The skills you'll need

To succeed in this role, you’ll bring a wealth of knowledge and experience in financial control, preferably gained within financial services. You’ll have worked in a global context and will have the ability to build and maintain strong working relationships with a variety of stakeholders in a changing environment. And you’ll hold a professional accounting qualification or have significant relevant experience in place of this.

You'll have experience in developing operating models, operational accounting and systems architecture solutions drawing on specific development skills and wider system experience.

We’ll also look to you to bring:

Practical experience in developing and documenting the end to end accounting models for Finance

A proven ability to build strong working relationships with a variety of stakeholders and customers across organisations and geographical boundaries, influencing and challenging as required

Up to date knowledge of accounting standards

Strong communication skills and the ability to clearly and succinctly articulate issues to senior management

Demonstrable commitment to continuous improvement activity

An astute eye for detail, with excellent analytical and problem-solving skills

Detailed knowledge of the end to end accounting models form source platforms to the General Ledger

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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.