Credit Risk Modeler / Data Scientist

 (3+ years exp)
Published: 3 weeks ago

Job Location

Remote • 
Europe • 
London • 

Job Type

Full Time

Visa Sponsorship

Not Available

Hires remotely

Everywhere

Relocation

Allowed

Hiring contact

Asher Ismail

The Role

Role Overview 🚀
We’re looking for a Data Scientist who has experience in creating credit risk models for SME businesses using mathematical and statistical techniques. We have a brilliant team of developers and we’re now keen to add our first data scientist to the team. Join us and help build the risk function of one of the hottest fintech companies in Europe, working alongside our founders to revolutionize how entrepreneurs are funded.

About Uncapped 👫
Uncapped is Europe’s first revenue-based finance provider. We believe founders shouldn’t have to give away ownership of their company to fund growth. That’s why we provide interest and equity-free investments from £10k to £1 million. We charge a flat fee of 6% on the capital provided and get repaid through a revenue share. There’s no pitches, cap tables or coffees required. So founders can apply online, receive an offer and start growing their business!

With offices in London and Warsaw, we’re backed by Europe’s top investors including Seedcamp, Global Founders Capital and Whitestar - early investors in other fintechs such as Transferwise, Revolut, and Funding Circle. We’ve raised £10m of investment to date and are ready to scale.

Your Mission ✍️

  • You will help further accelerate the Uncapped underwriting process
  • Improve our decision rules and credit scoring for SMEs
  • Develop scalable models using existing and alternative data sets Customise models for new country and product launches
  • Suggest and implement changes to credit policy and processes
  • Deliver enhanced insight and analytics for portfolio management / MI reporting
  • Collaborate with product owners and engineers to improve our data infrastructure and build a best-in-class technology platform

What skills you’ll need

  • Bachelors/Masters degree in a technical field (Machine Learning/ Mathematics/ Physics/ Statistics/ Computer Science preferred)
  • You have excellent analytical skills, including rigorous statistical knowledge, tempered with a sense of commerciality and business focus
  • Proficiency in developing production-level models for commercial lending
  • Familiarity with SME credit risk and the underwriting process
  • Proficiency in Python, Excel, SQL, and ideally R
  • Outstanding logic and problem solving
  • Ability to think creatively, generate innovative ideas, challenge the status quo
  • Strong communicator in English and comfortable working across different cultures
  • Can translate complex problems in simple terms to the business and senior management

Benefits 🎁
At Uncapped, we believe it’s the people that work here that makes us successful. We are a startup with big ambitions and we work hard so we want to give our people the benefits that they really want. We’re constantly adding to this as new people join but here’s a list of the sorts of things you can expect:

  • Competitive compensation plan
  • Company pension (UK employees)
  • Fun bi-monthly team outings - e.g. adventures include escape rooms, silent discos, comedy clubs, and mini-golf (to resume once social distancing restrictions are lifted)
  • Up to 2 weeks unpaid leave per year to pursue personal projects, travel or study (additional to standard holiday allowance)
  • Tech and cycle salary sacrifice schemes (UK employees)
  • Weekly recognition and awards
  • Opportunity to make a big impact every day on the lives of European entrepreneurs!

How to apply 🤔
Apply on Angelist or send your CV with a brief note telling us why you are excited about Uncapped and this specific role to [email protected]

We are not working with any recruiters, so please do not send us any applications.

More about Uncapped

Founders

Asher Ismail
Founder • 3 years • 5 years
United Kingdom
image
Piotr Pisarz
CEO & co-founder • 3 years • 5 years
London
image
Go to team image

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