The role
We are hiring a Strategy Analytics Manager or Senior Manager – Operations, with the final level determined by the successful candidate’s experience.
You will act as the COO’s go-to analytical partner, reporting to the CRO: combining strategic judgement, strong stakeholder management and hands-on technical delivery. This is both a management and coding role - you will lead a small team while personally delivering high-priority analysis using SQL and Python.
Key themes of the role
1. Operations MI, KPI and customer outcome metrics ownership
You will have full accountability for Operations management information and performance reporting.
You will:
Own MI 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.
You will:
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.
This includes:
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.
You will:
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.
Technical requirements
You must be highly hands-on and comfortable working directly with data.
Very strong SQL and Python
Experience working with APIs
Advanced Excel and strong 80/20 analytical judgement
Understanding of semantic data models and good analytics engineering practices
Basic statistics, experimentation and causal measurement knowledge
Understanding of Data Science, automation and LLM principles
dbt experience is helpful but not essential
Leadership and stakeholder skills
Strong commercial and operational judgement
High emotional intelligence and stakeholder management skills
Comfortable influencing and constructively challenging senior leaders
Able to translate complex analysis into simple business decisions
Capable of working at pace across several competing priorities
Team
You will initially manage:
Over time, you may hire an additional analyst and gradually grow the team based on business need.
You will set the direction and priorities of the Operations analytics function, develop the team and create an effective operating model across Analytics, Analytics Engineering, Data Science and Operations.