We’re building a credit bureau the right way - with the customer involved and transparent throughout. We're looking for a Research Scientist to tackle some of the most interesting and challenging problems in the world of finance in an evidence-based decision-making fashion. Our problems involve statistics, data science, machine learning (including NLP) but they are often not well-posed: a big part of this job will be thinking through what we actually want at a high level, and producing datasets and metrics that allow thorough and ongoing evaluation.
Our team has a diverse background
Not everyone studied Computer Science here and we have at least one classically trained opera singer. We have people with backgrounds in massive companies, small companies, and a couple for whom this is their first job. We’re looking for people who want to learn and grow; if that sounds like you, we’d love to hear from you.
We work closely together as a company
We’re a small team with a big vision, so no-one specialises too much - we wear many hats week-to-week. We’re grappling with a large problem so there are plenty of challenges to be faced but we face them one weekly sprint at a time. Your role here would see you working with the CTO and the Product team to bring your research into production.
You can work on some of the most challenging problems around
We're building a new kind of credit bureau, which means measuring financial behaviour in a way that's never been done before.
We process some of the most interesting data around - millions of financial transactions and account data - and your job would be to understand it and build upon it.
We want to help people avoid getting into financial situations that ruin lives. For you, that might mean understanding income patterns for every kind of employment out there, and how susceptible they are to shock. It might mean getting to grips with how debt affects people after they take it on. It might even be understanding the real state of the wider consumer economy! We want to understand risk and the kinds of financial behaviour that signal it. No small task!
You can work with a host of great technologies
To give you a flavour of our technical stack, we currently use:
- the scientific Python stack (e.g. numpy, scipy, pandas, Jupyter)
- machine learning libraries including TensorFlow, Keras, and scikit-learn
- Google's Cloud Platform for our learning & analytics infrastructure
(Our non-research stack is Ruby on Rails, Golang, Docker, Postgres, Amazon Web Services and Terraform.)
Should you apply?
(Yes!) We’re looking for people who:
- are excited by the work we’re doing
- would like to be engaged in meaningful work
- are keen to learn and develop their skills and knowledge
- are comfortable bottoming out problems in open discussion
- are deeply scientific
- are interested in building a data-oriented company
- can explain extremely complex topics in plain english
- love experimenting and testing hypotheses
What we value:
- Motivation, enthusiasm and passion for our mission to take on the big credit bureaus
- Expansive thinking, transparency, honesty and a good sense of humour
- Results and efficiency rather than hours in the office
What you’ll get:
- Competitive salary and stock options
- Flexible working arrangements, generous leave and a dog-friendly office. See full list of benefits - plus a bit more about working for us - here
- A ton of support, but an opportunity to run your own schedule and role
- The opportunity to develop your role and responsibilities as the company grows