Head of customer connections

Preston on the Hill
2 weeks ago
Create job alert

Head of Customer Connections
Our client exists to ensure the UK has the best full fibre networks, open to provide the best gigabit capable connectivity and broadband to UK businesses though a growing partner community.
The Role
Responsible for developing, implementing, and managing resource planning & control strategies to ensure optimal workforce allocation and operational efficiency. This dynamic role plays a key part in supporting business objectives by aligning resource capacity with customer demand, enhancing productivity, and driving cost efficiency.

Key Responsibilities
·Work Allocation & Scheduling: Prioritize tasks, ensuring SLA compliance across resource groups - Planning, Civils, Extensions, Wayleaves, Field, NOC, Contractors
·Work Control & Monitoring: Responsible for all daily orders planned and in process throughout each working day. Coordinating with internal and external teams to deliver output that supports on time delivery. Implement escalation procedures for unresolved or critical network issues.
·Production Scheduling: Creating schedules to ensure timely completion of tasks.
·Workforce Allocation: Ensure optimal deployment of resources across teams and regions to maximize productivity.
·Operational Efficiency: Identify process improvements to enhance workforce utilization, reduce costs, and improve service delivery.
·Customer Service Excellence: Ensure delivery of excellent customer service by providing proactive status updates on order journey and responding to customer inquiries and resolving issues efficiently and effectively.
·Data Analysis: Use data-driven insights to inform decision-making, ensuring resource levels align with performance targets.
·Stakeholder Management: Collaborate with senior leadership, operations teams, and HR to align resource strategies with broader business objectives.
·Reporting: Develop and maintain performance dashboards, providing visibility on resource utilization, demand trends, and KPIs.
·Risk Management: Identify potential resource shortfalls and implement contingency plans to mitigate disruption.
·Technology Integration: Lead the adoption and optimization of workforce planning tools and systems to improve forecasting accuracy and decision-making.

Key Skills & Competencies
·Strong analytical and forecasting skills with experience using data-driven insights.
·Expertise in telecoms resource planning, including network build, field operations, and customer support environments.
·Proven leadership experience with the ability to manage cross-functional teams.
·Excellent stakeholder management and communication skills.
·Strong organizational and problem-solving abilities.
·Proficiency in workforce management tools (e.g. Field Dynamics, Field Service Management etc) and data visualization platforms.

Qualifications & Experience
·Essential: Extensive experience in resource planning and workflow management, preferably in the telecoms sector.
·Desirable: Degree in Business, Operations Management or Data Analytics
·Proven track record in delivering effective resource planning strategies in a complex operational environment.
·Experience in managing large-scale workforce models and forecasting processes.

Key Performance Indicators (KPIs)
•Forecast accuracy, delivery rates, and resource utilization rates.
•Service level performance and adherence to customer SLAs.
•Cost efficiency improvements linked to resource planning decisions.
•Employee engagement and satisfaction within managed teams.

To apply, please send a copy of your CV and a covering letter to alex . drury @ nms recruit . com or, alternatively, submit your application via the link below

Important Information: We endeavour to process your personal data in a fair and transparent manner. In applying for this role, NMS Recruit will be acting within your interest and will contact you in relation to the role, either by email, phone or text message. For more information see our on our website. It is important you are aware of your individual rights and the provisions the company has put in place to protect your data. If you would like further information on the policy or GDPR please get in touch with us

Related Jobs

View all jobs

Senior Market Data Analyst - European gas

Data Analyst - Vessel Particulars & Companies Team Leader

Head of Data Science (Basé à London)

Head of Data Science

Head of Customer Safety (Property / Building Compliance)

Data Analytics Managers

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.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

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.