Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Subscription Revenue Manager

City of London
1 year ago
Applications closed

Related Jobs

View all jobs

Subscriptions Account Director - leading business intelligence platform (retail sector)

Senior / Lead Data Analyst, Strategic Finance (FP&A)

Senior Data Engineer/ Scientist

Data Architect - 12 Month FTC (we have office locations in Cambridge, Leeds and London)

A Subscriptions Revenue Manager is sought by one of the UK's fastest-growing SaaS businesses. A leading provider of a comprehensive communication platform with revenues already upwards of c. £150m and continued growth and acquisitions projected in the coming years, this newly created and exciting role offers a fantastic opportunity to drive growth and innovation within a dynamic environment.

Subscription Revenue Manager Responsibilities:

Subscription Revenue Management: Own, lead, and develop the comprehensive lifecycle of subscription revenue, focusing on new bookings and renewals, ensuring accurate revenue and Annual Contract Value (ACV) recognition and reconciliation.
Cross-Functional Subscription Oversight: Coordinate subscription management and revenue recognition processes across various teams, implementing new procedures aligned with the company's strategic goals for product launches, geographical expansions, or new verticals. Utilise subscription data to inform critical business decisions.
Subscription System Optimisation: Oversee and enhance the subscription management system within Salesforce, as well as the broader billing and ERP ecosystem, including NetSuite.
Financial Reporting and Analysis: Prepare and evaluate monthly, quarterly, and annual financial reports specific to subscription revenue, delivering insights that inform strategic planning.
Customer Retention Strategy: Collaborate with the Customer Success team to enhance renewal visibility and foster improved customer retention rates.
Data-Driven Insights: Employ data analytics to track commercial trends, uncover growth opportunities, and provide actionable recommendations.
Team Collaboration: Work in close partnership with sales, customer success, commercial, and finance teams to ensure alignment in revenue strategies and processes.

Candidates for the Subscription Revenue Manager will be:

Qualified Accountant (ACA/ACCA/CIMA)
Minimum of 3 years' experience in a similar role.
Hands-on experience of subscriptions and revenue recognition.
Knowledge of SaaS KPI metrics, mainly ACV.
Someone with gravitas to deal with stakeholders.

Salary & Package:

£70,000 - £80,000.
Discretionary bonus.
Private healthcare.
Flexible benefit scheme.
Hybrid working (a minimum of 2 days per week in my client's Central London office)

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.