Analytics Team Lead Data Operations

RealityMine has been a pioneer in delivering data driven insights to the world's largest brands for over a decade. Our platform provides unique data solutions to our clients enabling them to make strategic, informed decisions powered by data from real people, collected in a privacy safe way. As an AI-driven business, we actively invest in automation and AI-enabled approaches to scale insight, improve efficiency, and unlock new value from our data. With ongoing business growth, we are evolving our Data Operations function to ensure analytical work continues to be delivered consistently, efficiently, and to a high standard across the business. The Role As Analytics Team Lead, you will own the execution, prioritisation, and quality of analytical work across RealityMine. This role is responsible for ensuring analytics requests from clients, internal stakeholders, and Data Operations initiatives are clearly scoped, prioritised appropriately, and delivered to a consistent and trusted standard. This is a hands‑on leadership role. Alongside leading and developing a team of Data Analysts, you will remain actively involved in delivery, working directly on complex or high‑impact analytical work where judgement, experience, and context matter most. You will act as the primary point of ownership for analytical delivery and work closely with leadership and colleagues in Data Operations and across the business, to ensure analytical outputs align with agreed metrics, standards, and long‑term strategy. Our offices are in Trafford Park, Manchester and the role consists of hybrid working, where we ask for our team to be in the office for collaboration and team building a minimum of 2 days per week. The rest of the week is up to you; deep focus at home, or more of the same! Key Responsibilities Own the intake, scoping, prioritisation, and delivery of analytical work across clients, internal stakeholders, and Data Operations initiatives. Lead and develop a team of Data Analysts, while remaining hands‑on in the delivery of complex, high‑value analytical work. Translate ambiguous or open‑ended questions into well‑defined analytical problems with clear outputs, assumptions, and caveats. Ensure analytical outputs are consistent, well‑reasoned, and aligned with agreed business metrics and definitions. Act as a point of escalation for complex analytical questions, interpretation challenges, or conflicting conclusions. Work with peer Team Leads to identify analytical work that should be operationalised through dashboards, automation, or monitoring. Actively promote the use of automation and AI‑assisted tools to improve efficiency, reduce manual effort, and scale analytical delivery. Help embed an AI‑enabled mindset within analytics, encouraging experimentation while maintaining rigour and trust in outputs. Adhering to Company Policies and Procedures with respect to Security, Quality and Health