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

Apply Now

Head of RevOps - Remote

Zyte
Leeds
7 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Head of Data Architecture

Head of Data Architecture

Head of Business Intelligence - Leeds

Head of Data Products for Quantitative Strategies and Applications

Head of Data Products for Quantitative Strategies and Applications

At Zyte, we eat data for breakfast and you can eat your breakfast anywhere and work for Zyte. Founded in 2010, we are a globally distributed team of over 240 Zytans working from over 28 countries who are on a mission to enable our customers to extract the data they need to continue to innovate and grow their businesses. We believe that all businesses deserve a smooth pathway to data.

For more than a decade, Zyte has led the way in building powerful, easy-to-use tools to collect, format, and deliver web data, quickly, dependably, and at scale. And today, the data we extract helps thousands of organizations make smarter business decisions, secure competitive advantage, and drive sustainable growth. Today, over 3,000 companies and 1 million developers rely on our tools and services to get the data they need from the web.

Reporting to the CRO, you will lead and grow a RevOps team, shaping strategy, selecting technology to optimize our revenue generating processes. You will partner with our  Go-To-Market (GTM) .leadership to design and enforce the right sales processes and pipeline building workflows to drive efficiency and alignment across our GTM teams.

Beyond implementing the right tools and processes for efficiency, you'll collaborate across functions to drive alignment and identify the most impactful revenue optimizations. As the go-to leader for Sales, Customer Success, and Marketing, you will play a key role in driving revenue growth, improving operational efficiency and devising creative plans to support our business. 

Requirements

Roles & Responsibilities:

Team Leadership & Operations

  • Lead and grow the Revenue Operations team, overseeing planning, execution, forecasting, reporting, pipeline management, and strategic analysis across Sales, Marketing, and Customer Success.
  • Ensure high levels of quality, accuracy, and process consistency.

Systems & Data Management

  • Own the CRM and wider data architecture for GTM execution and reporting, Optimize all sales, CS, and marketing tools, with Salesforce (SFDC) as the central hub.
  • Evaluate, implement, and improve systems to enhance efficiency and data integrity.
  • Monitor and analysis metrics across the full revenue cycle. Build and rollout dashboard to show performance, trends and opportunities. 
  • Prepare operational reporting for GTM team. Present regular reports to leading highlighting issues and opportunities. Drive the GTM operational cadence. 

Forecasting & Strategic Planning

  • Develop and maintain reliable forecasting processes, ensuring alignment with Sales Leadership.
  • Drive annual planning, including budget goals, headcount models, territory planning, and variable compensation design, in partnership with Finance.
  • Manage budget performance and drive continuous process improvements.

Process Optimization & Cross-Functional Alignment

  • Design and refine processes for lead handoff, sales execution, marketing campaigns, and customer success strategies.
  • Support leadership with insights on pipeline, forecasts, retention, and revenue trends.
  • Ensure collaboration across teams to maximize efficiency and performance.

Strategic Projects & Execution

  • Lead and execute key strategic initiatives, such as ABM and Outbound, new GTM routes
  • Identifiy and drive change which delivers real business growth. 


Requirements:

Experience & Leadership

  • 7+ years in Revenue Operations, Sales Operations, or Strategic Sales roles within fast-paced, high-growth SaaS environments.
  • 4+ years leading an operations team, with proven ability to build and develop high-performing teams.

Problem-Solving & Decision-Making

  • Skilled in diagnosing and resolving complex issues while balancing immediate priorities and long-term needs.
  • Strong organizational and prioritization skills to effectively lead teams and drive initiatives.

Analytical & Technical Expertise

  • Excellent analytical skills to process large datasets and simplify insights for decision-making.
  • Deep understanding of SaaS KPIs, end-to-end revenue management, and reporting best practices.
  • Proficiency in BI tools (e.g., Tableau) is a plus.

Systems & Tools Proficiency

  • 5+ years of hands-on Salesforce experience, including admin capabilities (validation rules, process builders, object design, reporting).
  • Strong familiarity with sales and marketing tools; working proficiency in marketing automation platforms preferred.

Collaboration & Communication

  • Effective interpersonal and communication skills with a strong ability to lead cross-functional teams.

Benefits

By joining the Zyte team, you will:

  • True remote working - we believe great work can happen anywhere.
  • We pride ourselves in our strong remote culture.
  • We are building something great together - join our passionate, ambitious team in a fast-paced environment where you are valued 
  • If you want to make an impact and be part of something exciting, we would love to meet you! 

At Zyte, we value diversity and flexibility. As a fully remote company since 2010, we’re ready to adjust our processes to meet your unique needs. If you need assistance during the application process, please contact our Talent team.

Learn more about us on ourMeet Zytepage.

We are an equal opportunity employer, considering all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, disability status, or any other protected characteristic. We are committed to a welcoming and supportive environment for everyone. We look forward to learning more about you and exploring how we can grow together!

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.

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.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.