iwoca
Hiring now
Data Scientist - Partner Flow Team
Hybrid · London, England, United Kingdom£70k–100kFull-timePosted 2 weeks ago
iwoca
Applyiwoca
Hiring now
Hybrid · London, England, United Kingdom£70k–100kFull-timePosted 2 weeks ago
iwoca
ApplyHybrid in London, United Kingdom
We're looking for a Data Scientist to join the Partner Flow team.
You'll use experiments and causal inference to shape how iwoca grows through its partners – the fintechs and platforms that offer iwoca lending inside their own products.
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
Partner Flow owns the journey for small businesses that come to iwoca through a partner platform, from how they discover iwoca’s business finance to any repeat lending. The aim is to reach each business at the right time, make it easy to apply and get funded, and match them with the offer that suits them and works best for iwoca over time.
The team works on three parts of that journey:
The application. Making it smooth and collecting the data a credit decision needs.
Routing. Working out which applications get an automatic decision and which need input from a credit analyst.
Offer terms. Testing amount, duration, and interest rate, working closely with Credit Risk Modelling, who build the credit models.
The team is small and cross-functional – data science, engineering, design, and product – and works across the full application stack, from the APIs partners integrate with to the experience customers see when they apply.
The role
As the Data Scientist in Partner Flow, you'll run the analysis behind the team's product decisions. Most of it is experiment design and causal inference, with some model building and funnel analysis.
You'll own each project from the start. You'll work out what the business needs, reason from first principles, weigh the trade-offs, and shape the project with product, commercial, and strategy colleagues before deciding how it gets done. The team's analytical approach is still young, so you'll help set its methods. Around 10% of your time is for research and learning – finding better methods for the problems in front of you, or new ways to add value.
You'll work with data scientists in iwoca's other customer flow teams, and join the analytics guild – iwoca's data science community – to align on methods and build your expertise. Your results reach the wider business through Learnings – short write-ups of what an experiment found, shared at weekly and fortnightly sessions.
Live project examples:
Pre-qualification. Measuring how showing customers what they could borrow before they apply affects conversion and Customer Lifetime Value (CLtV), then shaping how the model behind it develops.
Credit cards. Working out which customers should see iwoca's recently launched credit card, a Flexi-Loan, or both – and whether the card wins extra customers or takes them from Flexi-Loan.
Top-up notifications. Measuring whether letting eligible customers know they can borrow more increases CLtV, using causal inference methods beyond a standard A/B test.
Partner funnel. Building a clear view from application to drawdown, finding where customers drop off, and testing fixes where they'll matter most.
The requirements
Essential:
Statistical foundations. You have a background in probability and statistics from a quantitative field – typically a degree or Master's in Statistics, Mathematics, Physics, Engineering, or similar. You reason about uncertainty and calibration as first-order concerns.
Causal inference and experimentation. You have designed and analysed experiments where separating signal from noise mattered – A/B tests, quasi-experiments, or lift studies. You know where A/B testing breaks down and what to reach for instead.
Commercial experience. You have used data science to shape commercial decisions – in an industry role, a consultancy, or a substantial placement – and worked alongside the people who acted on them.
Analytical ownership. You have taken loosely defined problems from start to finish – working out the right question, choosing the approach, and seeing the analysis through to a decision.
Iteration. You make the best call the current evidence allows and act on it early. As new data comes in, you update the call and tighten the answer.
AI leverage. You've used AI to produce work you couldn't have delivered alone – an analysis pipeline, a prototype, or a tool others use. You judge where it helps, and you check its output before anyone acts on it.
Communication. You write and speak clearly, directly, and concisely. You adapt technical detail for non-technical colleagues in commercial and strategy roles.
Bonus:
Causal inference beyond A/B testing. You have used synthetic control, interrupted time series, or difference-in-differences in commercial or research work.
Bayesian methods. You have used hierarchical models, MCMC, or Bayesian updating in real work.
Funnel and marketplace experience. You have analysed conversion funnels or marketplaces where products compete for customers' attention.
Market curiosity. You've explored how the partner lending market works – what makes a partner choose iwoca over a competitor, and what makes a customer convert.
Coding. You can write code for analysis. The team works in Python.
The salary
We expect to pay from £70,000 to £100,000 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, 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: