Business Continuity Manager

Brambles Holdings (UK) Limited
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Technical Engineer

Undergraduate Intern - Data Science

Business Data Analyst

Data Engineer

Interim Head of Data & Analytics

Business & Data Analyst

We are expanding our Business Continuity team, looking to bring in a BCM Business Continuity Manager. The role will support the global programme with programme management,administrative, change management and reporting activities with senior leadership visibility. Our global programs work across 60 countries and every region. The focus is implementing a Global BCM Framework and IT system aligned to ISO22301.

The role will serve as a critical link between business needs and technology solutions by identifying, analysing, and documenting requirements. Youll ensure that the developed solutions are aligned with business objectives and delivers value while effectively managing stakeholder expectations.


Key Responsibilities may include:

    • Collaborate with a wide range of stakeholders to identify, analyse, document, and prioritize business, functional, and non-functional requirements, ensuring alignment with project goals.
    • Lead feasibility studies and produce business models, business cases, usability requirements analysis, and evaluation to support strategic initiatives.
    • Identify and raise issues that could impact the execution of strategic, operational, or project plans, providing timely recommendations for resolution.
    • Communicate effectively with business stakeholders, project managers, product owners, systems analysts, developers, and quality assurance analysts to ensure requirements are clearly stated, understood, and actionable.
    • Oversee end-user testing, tracking progress, and ensuring timely defect resolution to meet quality standards.
    • Present complex technical information in an understandable way to both technical and non-technical audiences, simplifying complex ideas to facilitate decision-making.

What youll need:

Experience with ISO22301 and BCM frameworks

Demonstrated experience in managing and influencing others, it is required to work
together with other members from various regions and areas.

Strong understanding of business metrics

Experience in data analyst

Strong communication & Interpersonal skills (written, verbal, and presentation skills)


JBRP1_UKTJ

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.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.