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Salary
$92k – $131k per year
Location
Hybrid (London, United Kingdom)
Visa
Licensed UK visa sponsor
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 13, 2026. iwoca scores B on the Alion truth index.

Overview
Company
Impact
Profile match
iwoca is a financial technology lender that provides flexible short-term business loans, revolving credit lines and buy-now-pay-later financing to small businesses in the United Kingdom and Germany. Founded in 2012, it uses its own data and risk models to make fast lending decisions and has extended billions of pounds of credit to small firms. The company is headquartered in London, England, United Kingdom.

Data Scientist - Broker Flow Team

Hybrid in London, United Kingdom

We're looking for a Data Scientist to join the Broker Flow team.

You'll own the experiments that shape the journey brokers use to apply on their clients' behalf. Brokers are one of iwoca's main routes to new customers.

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

Broker Flow, a new team in iwoca's third-party acquisition department, owns the journey for businesses that come to iwoca through a broker - from before they apply to a completed credit assessment. Its aim is to get more of those businesses to an offer. Broker Terms, a separate team, then sets the price, amount, and duration of each offer.

The team works on three parts of that journey:

  • Broker engagement. Working with brokers and their clients before an application starts.

  • The application. Making it smooth to complete, and collecting the data a credit decision needs.

  • Operations. Running the CRM tools iwoca's teams work in, and automating operational processes.

The team is small and cross-functional - commercial strategy, engineering, design, and data science - and works across the full application stack, from the Broker API to the Introducer Portal brokers use.

The role

As the Data Scientist in Broker Flow, you'll give the team the evidence behind its product decisions. The core of the work is experiment design and causal inference, with modelling and analysis alongside it.

You'll own each project end to end. You'll frame the problem, choose the method, build the model or run the test, and take the answer to the commercial and strategy colleagues who act on it. You'll also meet brokers in person, which gives you the context to ask the right questions. The team is new, so its methods are yours to shape. You'll see the effect of your work in how many businesses reach an offer, and in their lifetime value.

You'll work with data scientists in iwoca's other broker and partner teams, and join the analytics guild - iwoca's data science community - to compare methods and build your expertise. Your results reach the wider business through Learnings, short write-ups that iwoca shares at weekly and fortnightly sessions.

Live project examples:

  • Refinancing. Modelling which businesses would benefit from refinancing their existing borrowing, and testing a product for them.

  • Stalled applications. Finding where broker applications stall, and testing fixes - from clearer emails and portal updates to an early offer that encourages document upload.

  • Reintroductions. Testing the best moment for brokers to bring existing iwoca customers back to borrow.

  • Approval probability. Measuring how well the estimate brokers see in the Introducer Portal predicts actual credit decisions, and making it more accurate.

  • Measuring impact. Designing early signals - at sign-up and once documents are in - that predict a business's lifetime value, so the team can judge its changes quickly.

The requirements

Essential:

  • Statistical foundations. You have a background in probability and statistics from a quantitative field such as mathematics, physics, or statistics. You're comfortable with Bayesian reasoning, and have applied hierarchical models or formal decision-making under uncertainty in real work.

  • Causal inference and experimentation. You've separated signal from noise in observational and experimental data. You know where A/B testing breaks down and what to reach for instead.

  • Analytical ownership. You take loosely defined problems from start to finish - framing the question, choosing the method, and landing the answer with the people who act on it.

  • Data tooling. You're proficient with data manipulation and modelling tools, and with scientific computing libraries.

  • AI leverage. You've used AI to produce work you couldn't have delivered without it - an analysis pipeline, a prototype, or a tool others use. You judge where it helps and where it doesn't, 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:

  • Modelling depth. You've built or adapted statistical or ML models and can explain the maths behind them.

  • Stochastic methods. You've used stochastic processes for inference or time-series modelling.

  • Broker market insight. You've worked with brokers or other intermediaries in lending or financial services.

  • 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:

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