Tech Lead - Decision Technology
Hybrid in London / Remote within the UK
The company
Small businesses move fast. Opportunities often don’t wait, and cash flow pressures can appear overnight. To keep going, and growing, SMEs need finance that’s as flexible and responsive as they are.
That's why we built iwoca. Our smart technology, data science and five-star customer service ensures business owners can act with the speed, confidence and control they need, exactly when it's needed.
We’ve already cleared the way for 100,000 businesses with more than £4 billion in funding. Our passionate team is driven to help even more SMEs succeed, through access to better finance and other services that make running a business easier. Our ultimate mission is to support one million SMEs in their defining moments, creating lasting impact for the communities and economies they drive.
The team
The Credit Risk team builds and maintains the technology and models that determine who iwoca lends to, how much, and on what terms. Their work covers credit scoring, scorecard development, approval thresholds, and portfolio monitoring – all working to maximise lending volume without taking on disproportionate risk.
The team has nine data scientists, four engineers, and two strategy analysts. The data scientists analyse past data and make the models; the engineers build and maintain the supporting infrastructure; and the strategy analysts translate model outputs into lending decisions.
The role
As Tech Lead, you’ll be responsible for the engineering systems that underpin Credit Risk modelling at iwoca. You’ll focus on the platform, pipelines, and production systems around the models, rather than building models yourself. This is a hands-on technical leadership role, combining technical direction, line management, and individual contribution.
Technical leadership
- Lead four engineers working on the modelling platform and surrounding systems; help the team deliver high-quality solutions.
- Raise engineering standards across modelling systems and infrastructure, with a focus on reliability, observability, reproducibility, and safe change.
- Set technical direction by understanding adjacent systems, workflows, and constraints to identify the right problems to solve at the right time.
Individual contribution
- Stay hands-on in the codebase, especially when the team is dealing with ambiguity, cross-system complexity, or problems without an obvious owner.
- Lead by example in how problems are approached and how rigour is balanced with speed of delivery.
- Contribute directly to the systems that matter most, making pragmatic changes that reduce friction, strengthen the platform, and improve reliability in production.
Work that matters
- Engineering decisions in this area directly affect the accuracy of our credit decisions and the volume of lending iwoca can responsibly support.
- Better infrastructure leads to faster experimentation and better models
- Help the team to work faster and with more confidence in the platform. Work with data scientists and strategy analysts to maintain the feedback loop between analysis, strategy and engineering.
The salary
We expect to pay from £100,000 - £160,000 for this role. But, we’re open-minded, so definitely include your salary goals with your application.
The culture
At iwoca, the best idea wins. We model our culture on independent thinking, challenging untested logic, and evidence-based decisions. We prioritise learning and growth, and give people the autonomy to develop in the direction that makes them most effective.
We're a tech company and believe in the power of AI to help us work faster and better. We provide the infrastructure where every iwocan always has access to the best models and where those models have access to all of our data. We will help our people to learn how to use and grow with the new tools available to them.
The offices
We put a lot of effort into making iwoca a great place to work:
- Offices in London, Leeds, Berlin, and Frankfurt with plenty of drinks and snacks.
- Events and community-led groups, including running groups, padel, and monthly ping-pong and pool competitions.
The benefits
- Flexible working hours.
- 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 per year, 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 external counselling and therapy sessions for team members that need emotional or mental health support.
- 3% Pension contributions on total earnings.
- An employee equity incentive scheme.
- Generous parental leave and a nursery tax benefit scheme to help you save money.
- Electric car scheme and cycle to work 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:
The requirements
Essential:
- Advanced proficiency in software development.
- Experience building and shaping large systems in complex business domains.
- Experience building robust systems where the 'product' is high-quality data and you can 'speak the language' of analysts and data scientists.
- Confidence to work closely with partners from other disciplines to challenge assumptions and discover underlying problems.
- Demonstrable leadership skills: you have mentored juniors and inspired teams to deliver cross-functional projects. You can balance hands-on coding with strategic planning.
- You use AI (like Cursor, Claude Code or similar) in your daily flow—whether for work or for fun. You use it to blast through boilerplate and research, so you can focus on the hard parts: complex architecture, rigour, and high-stakes decision-making.
Bonus:
- A strong numerical or technical background, ideally with a degree in physics, engineering, maths, computer science or a related field
- Experience building and maintaining analytics systems
- Experience with Python, Snowflake, or PostgreSQL
- Experience working on feature-management systems such as feature services or features stores
- An understanding of complex data systems, including event-sourced data models
