lendable logo light transparent
  • Careers Home

  • Jobs

  • Blog

Chief Placeholder Officer

  • London
  • Full Time (Permanent)
  • Hybrid
  • Placeholder team
Apply for this role

About this role

Suspense thrives on uncertainty, a calculated pause that draws in the observer. In this pause, placeholders emerge as valuable cues. Their very presence suggests that what is yet unseen could hold the answers, a revelation or a solution. When used thoughtfully, a placeholder can tease and compel, engaging the imagination.

Responsibilities

In websites, a loading spinner is no different than the ellipsis of a suspenseful plot twist; it tells the viewer that what is coming is worth waiting for. Key benefits of effective placeholders include:

  • Maintaining engagement: By signaling more to come, placeholders prevent user drop-off.
  • Setting expectations: Clear, well-placed placeholders hint at what content is coming next, adding structure.
  • Building suspense: The anticipation of more content holds attention, just as in storytelling.

Placeholder content, however, must tread a careful line. Too sparse, and it risks undermining its own suspense; too dense, and it overwhelms with unnecessary clutter. The balance lies in leaving just enough room for the mind to wander and fill the gaps.

© Lendable 2026
  • Careers Home
  • Jobs
  • Blog
  • IER Disclosure

Strategy Analytics Manager

  • London
  • Full Time (Permanent)
  • Hybrid
  • UK Operations Analytics
Apply for this role

About the role

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:

  • One Senior Analytics Engineer

  • One Analytics Engineer

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.

Apply for this role

About Lendable

A large group of around 50 people, and one dog, in an office facing the camera and smiling

Lendable is on a mission to build the world's best technology to help people get credit and save money.

  • Founded in 2014

  • Profitable since 2017

  • Unicorn in 2021

  • Backed by Balderton, Goldman Sachs and Ontario Teachers' Pension Plan

  • Loved by customers & employees with top reviews on Glassdoor and Trustpilot

So far, we’ve rebuilt the big three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do. We’re going after the two biggest Western markets (UK and US) where trillions are held by big banks with dated systems and painful processes.

Apply for this role

Life at Lendable

Two people with laptops on their lap sat either side of a black labrador on a sofa in front of a window. The dog is a very good girl.
  • The opportunity to scale up one of the world’s most successful fintech companies

  • Best-in-class compensation, including equity

  • You can work from home every Monday and Friday if you wish - on the other days we all come together IRL to be together, build and exchange ideas

  • Our in-house chefs prepare fresh, healthy lunches in the office every Tuesday-Thursday

  • We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance

  • We're an equal opportunity employer and are keen to make Lendable the most inclusive and open workspace in London

Check out our Glassdoor Reviews