Credit Kudos is a venture-backed fintech startup and challenger credit bureau that uses financial behaviour to measure creditworthiness. Our technology transforms the way credit checking and credit scores work by generating a more accurate and holistic view of a borrower's creditworthiness. We're working with lenders to help them make better, fairer credit decisions and with consumers to help them access fair, affordable credit.
*About the role:*
Credit Kudos is looking for a Data Scientist. We're building a new kind of credit score powered by real financial behaviour. We're looking for a motivated, enthusiastic data scientist who is interested in modelling financial behaviour to improve the financial resilience of consumers and help democratise access to mainstream financial services.
Credit plays an integral role in society and without accurate credit scoring we predict a huge section of the population will be unfairly excluded. We're democratising access to credit and removing these false negatives. You'll be breaking new ground at the very heart of the business, making decisions that will steer lending outcomes for hundreds of thousands of people.
* Put simply, you'll be analysing financial transaction data to understand what factors contribute to credit-worthiness
* We're building fair models of risk that are backed up by facts, so you'll be utilising machine learning and predictive analytics to detect patterns in real financial behaviour that lead to defaults in loan repayments
* Lending is as much about financial health as it is about propensity to repay, so you'll be deconstructing and explaining your models to help consumers increase their financial resilience
* As experimentation evolves, previously unknown ideas could likely have business impact, so you'll be prototyping internal tooling for future experimentation
* Data Science is an expansive field, so you'll have the freedom to explore scientific research in work and during dedicated personal development time
* Collaborating with the research science team to learn and build upon your data science skillset
* Grounding in statistics/CS theory and core Machine Learning principles
* Can take a large dataset and answer key business questions in a repeatable, testable manner
* Work in a scientific manner, establishing hypotheses, success criteria and conducting relevant experiments
* Experience developing and testing data science models, experience in relevant technology stacks, e.g. R, Python (pandas, scikit-learn), SQL etc.
* Some experience in building APIs or backend services useful but not required
* Ideally 2-4 years experience working in a commercial setting in the data science field
* A Competitive salary with stock options.
* A Workplace pension.
* Flexible working arrangements with 2-3 days in office.
* MacBook Pro and equipment.
* Generous leave, a total of 36 days (inc Bank Holidays)
* A dog-friendly office.
* Cycle to work scheme.
* Office space at WeWork with bike shed, barista, fruit, etc.
* 30 minute screening interview on Google Hangout
* 45 minute CV interview going through your CV on Google Hangout.
* 1 hour technical interview with take home test in Python.
* 1 hour team interview with Product Manager and Chapter Lead
Python, PyTorch, Machine Learning, Data AnalysisPython, Flask, PyTorch, Pandas, Scikit, SQL, R, APIs