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

Apply Now

Data Analyst (Lending Strategy)

Iwoca
City of London
2 days ago
Create job alert
Data Analyst (Lending Strategy)

Hybrid in London, United Kingdom


The company


Imagine a world where every small business has the power to thrive. That's the world we're building at iwoca. Small businesses aren't just statistics – they're the heartbeat of our communities, the character of our high streets, and the engine of our economy. Since 2012, we've revolutionised how these businesses access finance, turning what was once a lengthy, frustrating process into something remarkable: funding that's fast, flexible, and actually works for modern businesses.


Our impact speaks for itself: we've provided billions in funding to more than 150,000 businesses across Europe, making us one of the continent's leading fintech innovators. But we're just getting started. Our mission? To empower one million businesses with the financial tools they deserve.


We combine cutting‑edge technology and data science with genuine human understanding to make finance feel less like a barrier and more like a superpower. Whether a business is managing cash flow or seizing unexpected opportunities, we ensure they get the funds they need – often within minutes.


The team


The Credit Risk Modelling team builds and improves the models that drive iwoca’s lending decisions. They combine data science, engineering, and risk expertise to balance automation with human judgement, and their work supports everything from underwriting and pricing to portfolio monitoring. The team’s work is central to iwoca’s growth and has a direct impact on both customer outcomes and business performance.


The team includes eight data scientists, two developers, and three lending strategy data analysts, all working hybrid schedules in London. The team’s work is quite collaborative and there’s always four or five people in the office on a given day. The team plans objectives for each quarter and manages progress with weekly meetings. They also have standups every other day to share concerns and help each other.


The role


You’ll analyse data and contribute to the development of our credit models for the enhanced underwriting segment. You’ll work with analysts, data scientists, and senior stakeholders to shape iwoca’s lending strategy.


Learn:



  • Build expertise in the credit domain.


  • Develop your analytical skills through exposure to different experimental approaches and complex analysis.



Develop commercial influence:



  • Practice turning data into information, and information into insights, so that you and various stakeholders can deliver improvements with real impact for our customers.



Work on interesting and impactful projects, for example:



  • Monitoring and refining risk models to improve decision‑making and portfolio outcomes


  • Analysing portfolios and tests to investigate credit performance, identify drivers of change, and adapt lending strategies


  • Improving our data, systems, and workflows to strengthen underwriting and monitoring


  • Supporting new product launches and adapting policies to meet investor and regulatory needs



The requirements


Essential:



  • A quantitative background, such as a degree in mathematics, statistics, economics, engineering, or a related field


  • Ability to analyse data and generate insights to support decisions


  • Ability to evaluate underwriting processes and improve credit models or policies


  • Clear written and verbal communication, with the ability to tailor analysis and recommendations to different audiences


  • A team player, with the ability to work confidently and enthusiastically with different people and teams



Bonus:



  • Experience in B2B or B2C credit risk, lending, and strategy


  • Proficiency in SQL and Python


  • Experience with data visualisation tools like Looker



The salary


We expect to pay from £40,000–£55,000 for this role. But, we’re open‑minded, so definitely include your salary goals with your application. We routinely benchmark salaries against market rates, and run quarterly performance and salary reviews.


The culture


At iwoca, we prioritise a culture of learning, growth, and support, and invest in the professional development of our team members. We value thought and skill diversity, and encourage you to explore new areas of interest to help us innovate and improve our products and services.


The offices:


We put a lot of effort into making iwoca a brilliant place to work:



  • Offices in London, Leeds, Berlin, and Frankfurt with plenty of drinks and snacks


  • Events and clubs, like bingo, comedy nights, yoga classes, football, etc.



The benefits:



  • Medical insurance from Vitality, including discounted gym membership


  • A private GP service (separate from Vitality) for you, your partner, and your dependents.


  • 25 days’ holiday, an extra day off for your birthday, the option to buy or sell an additional five days of annual leave, and unlimited unpaid leave


  • A one‑month, fully paid sabbatical after four years.


  • Instant access to emotional and mental health support.


  • 3% Pension contributions and share options.


  • Generous parental leave and a nursery tax benefit scheme to help you save money.


  • Cycle‑to‑work scheme and electric car scheme.


  • Two company retreats a year, we’ve been to France, Italy, Spain, and further afield.



And to make sure we all keep learning, we offer:



  • A learning and development budget for everyone.


  • Company‑wide talks with internal and external speakers.


  • Access to learning platforms like Treehouse.



Useful links:



  • iwoca benefits & policies


  • Interview welcome pack



#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

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.