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iwoca

Flexible SME loans and invoice financing

Data Scientist - Broker Terms

Data ScienceConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • 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.
  • 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. You have experience with careful experimental design to facilitate clean, trustworthy results.
  • 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.
  • You're proficient with data manipulation and modelling tools, and with scientific computing libraries (pandas, numpy, sklearn, PyMC).
  • 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.
  • You write and speak clearly, directly, and concisely. You adapt technical detail for non-technical colleagues in commercial and strategy roles.

Responsibilities

  • You'll model expected customer take-up rates, design experiments, and translate findings into pricing and product decisions for the acquisition channel that drives the most customer lifetime value (CLTV). Because the Broker Terms team is a young team, you'll influence how its analytical approach develops, not just what it produces.
  • You'll model how customers respond to offer terms and how brokers make decisions under uncertainty. You'll design experiments where causal inference is central: you'll need to know where standard A/B testing breaks down and what to reach for instead.
  • You'll work with commercial and strategy colleagues and see your analysis applied directly in day-to-day decisions. That includes meeting brokers in person – gaining context that shapes how you frame and interpret results – and coordinating with adjacent teams responsible for underwriting decisions, repeat lending, and offer construction.
  • You'll think across the full broker-referred customer journey – from first funding to repeat – identifying what drives CLTV and what changes to offer terms or UX improve it. You own both the strategy and the mechanism, so your findings feed directly into what the team builds and tests.
  • You'll use AI to accelerate and automate your analytical work – not occasionally, but as a default. You should have a view on where it genuinely helps and where a different approach is better.

Desired Qualifications

  • You've built or adapted statistical or ML models and can explain the maths behind them to commercial stakeholders.
  • You've used stochastic processes for inference or time-series modelling.
  • You've worked with brokers or other intermediaries in lending or financial services.

About the Company

iwoca

Flexible SME loans and invoice financing

Iwoca provides financing for small and medium-sized UK businesses, offering flexible loans and invoice financing to help with cash flow and growth. Its products include the Flexi Loan, which lets a business borrow with adjustable repayment terms, and iwocaPay, an invoice-financing service that lets customers pay invoices over time. The company runs its lending through a tech-driven platform that analyzes data and uses machine learning to assess credit risk and make quick decisions, often within 24 hours. This speed and flexibility set it apart from traditional lenders, as it focuses on tailoring financing to each SME’s needs rather than offering one-size-fits-all products. Overall, its goal is to enable smaller businesses to manage cash flow, access capital quickly, and support business growth.

Company size
501-1,000
Company stage
Debt Financing
Total funding
$2.2B
Headquarters
London, United Kingdom
Founded
2011

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