lendable - Strategy Analytics Manager

• 1. OPERATIONS MI, KPI AND CUSTOMER OUTCOME METRICS OWNERSHIP • You will have full accountability for Operations management information and performance reporting. • Own data across front-office and back-office Operations departments • Define and govern KPIs covering demand, SLAs, throughput, productivity, quality and customer outcomes • Ensure operational efficiency is balanced with fair, timely and effective outcomes for customers • Identify where operational processes or service performance are creating customer friction, repeat contact or poor outcomes • Ensure reporting is accurate, consistent and trusted by senior leadership • Develop strategic north-star metrics that show whether Operations is becoming more effective and scalable • Move the function beyond retrospective reporting towards forward-looking insight and decision support • 2. WORKFLOW OPTIMISATION AND OPERATIONAL STRATEGY • You will work closely with Operations Directors, Heads of Department, the Operations Transformation Office and Product teams to identify, prioritise and deliver the highest-value operational opportunities. • Diagnose bottlenecks, failure demand, customer friction and inefficient workflows • Work with Transformation and Product to define which problems and opportunities to pursue • Identify the lowest-hanging fruit and quantify the potential operational and customer value • Recommend improvements to processes, routing, tooling, products and ways of working • Define clear hypotheses, baselines and success measures before changes are implemented • Measure realised impact precisely and determine whether initiatives should be scaled, adjusted or stopped • Translate analysis into clear decisions, actions and ownership • 3. DEMAND, SLAS AND RESOURCING • You will own the analytical cycle supporting operational planning and performance decisions. • Understanding changes in demand and customer contact behaviour • Supporting forecasting, capacity and headcount decisions • Evaluating SLA and service-level trade-offs • Measuring throughput and productivity consistently • Identifying emerging risks or operational pressure points • Helping leaders make evidence-based prioritisation and resourcing decisions • You will be expected to explain not only what happened, but why it happened, what should change and how success should be measured. • 4. AUTOMATION, AI AND STRATEGIC MEASUREMENT • You will partner closely with Data Science and Operations teams to assess the impact of automation, AI and LLM-led initiatives. • Define hypotheses, baselines, control groups and success metrics • Measure time saved, quality improvements, risk reduction and customer impact • Identify unintended consequences or displacement of work • Prioritise automation opportunities based on value and feasibility • Ensure claimed benefits are supported by credible measurement • You will also develop an understanding of the regulatory environment surrounding fintech Operations, including complaints, vulnerability, fraud, PEP and sanctions screening, customer due diligence and conduct risk.