Data Scientist (Risk)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

We approach Data Science at Revolut the same way that we approach everything else – with class, logical thinking and lots of style

Let’s break it down: we take the most complex problems and create tailor-made solutions for our customers

If you’re thinking the Data team is kept in some sort of a secret den, doomed to never see the impact of their work, don’t worry - that’s not how we do things. They’re some of our best and brightest problem-solvers, deployed to the front lines to work in product teams and deliver rockstar solutions

What you’ll be doing

• Assessing and managing Risk by developing policies, methodologies, models and systems for Risk quantification, reporting and monitoring
• Developing and maintaining policies and methodologies for Risk Modelling
• Building models for Expected Credit Losses
• Building models for Stress Testing
• Building models for Capital Calculations
• Building systems for Risk quantification, reporting and monitoring

What you'll need

• Academic background in one of the following: Mathematics, Statistics, Economics, Machine Learning, Computer Science or Engineering
• Fluency in SQL
• Knowledge of both functional and OOP in Python
• Knowledge in Mathematics and Statistics including: Linear algebra, Dynamic systems and state-space representations, Markov chains & Time series statistics including VaR, GARCH, stationarity and cointegration
• Familiarity with Risk Theory and Financial Products in at least one of the following Risk areas: Credit, Counterparty, Market, Liquidity, Operational
• Experience in the Financial Sector

Nice to have

• PhD and research experience in a relevant field
• Record of contribution to personal and open source projects in GitHub
• Record of contribution to programming and statistical forums such as StackOverflow and Stats Stack Exchange