At a Glance
- Tasks: Own and develop credit models to support SMEs with flexible funding.
- Company: Join iwocaPay, a tech company dedicated to empowering small businesses.
- Benefits: Enjoy competitive salary, health insurance, generous holiday, and equity incentives.
- Other info: Dynamic team culture with opportunities for personal and professional growth.
- Why this job: Make a real impact on SMEs while working with cutting-edge data science technology.
- Qualifications: Experience in supervised machine learning and strong statistical foundations required.
The predicted salary is between 56700 - 69300 £ per year.
Hybrid in London, United Kingdom We're looking for a Data Scientist to join the iwoca Pay Risk Squad You'll own credit models that decide who iwoca Pay can safely fund and on what terms.
The team is small, the product is growing, and you'll shape how risk modelling is built – not just maintain what exists.
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.
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.
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 functioniwoca's Data Scientists specialise in supervised machine learning, statistical inference and exploratory data analysis, focusing on tabular and time series data.
The Risk Squad owns the automated credit decisioning and fraud prevention models that influence every lending decision the product makes.
The squad also handles counterparty risk, portfolio-level strategy, and ongoing monitoring of losses, chargebacks, and segment performance.
The role You'll co-own the full credit modelling stack with one other data scientist.
You'll collaborate on model design, review each other's work, and choose what to prioritise.
Your models directly control which small businesses get access to funding, on what terms, and how far the product can grow.
Real influence You own the models end to end, and your decisions carry commercial weight.
Expertise in supervised machine learning on tabular data, with experience building and iterating production models end to end (exploration through deployment and monitoring).
Strong statistical foundations in probability, uncertainty quantification, model calibration, and in reasoning about where a model is likely to be wrong.
Ability to work independently in a messy, early-stage environment – scoping problems, building infrastructure, and shipping models autonomously Pragmatism about what 'good enough' looks like commercially, balanced with rigour on high-stakes models.
Data engineering capability – building pipelines and managing datasets alongside the modelling work.
AI fluency – using AI to build, automate, and accelerate substantive analytical and engineering work.
Clear communication – you can adapt technical detail for non-technical colleagues working in product, risk, and leadership.
Bonus: Experience with credit risk modelling or financial services lending.
Experience with non-linear models (gradient boosting, neural networks on tabular data) in production settings.
Python proficiency – it's what the team uses day to day. We routinely benchmark salaries against market rates, and run quarterly performance and salary reviews.
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.
Events and community-led groups, including running groups, padel, and monthly ping-pong and pool competitions.
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 buy up to ten more days or up to five, 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.
Risk Data Scientist in London employer: iwoca
At iwoca, we pride ourselves on being an exceptional employer that champions innovation and collaboration. Our vibrant work culture fosters growth and creativity, empowering employees to make impactful decisions that drive the success of small businesses. With a commitment to professional development and a focus on leveraging cutting-edge technology, we offer a unique opportunity for individuals to thrive in the dynamic fintech landscape of London.
StudySmarter Expert Advice🤫
We think this is how you could land Risk Data Scientist in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like iwoca!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Risk Data Scientist at iwoca.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like iwoca.
✨Apply Directly through Our Website
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We think you need these skills to ace Risk Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at iwoca, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at iwoca. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at iwoca
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at iwoca!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
