RiverBank is a specialised lender dedicated to financing Small and Medium Enterprises and Real Estate firms in the Netherlands, Germany and France. RiverBank operates under a full European Banking License.
RiverBank's mission is to combine the best of the fintech and banking world. As experienced bankers, we commit the bank's balance sheet to grant loans which we analyze using a fundamental credit approach. As a fintech player, we digitally source, process and monitor the loans. Riverbank is growing fast both organically and through acquisitions.
As a young company, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team work. RiverBank will offer an entrepreneurial environment within the regulatory banking framework - a place for people to learn, to achieve and grow. Our culture will promote diversity and individual perspectives in an international environment, represented by more than 15 nationalities.
RiverBank is recruiting an ambitious Senior Quantitative Risk Analyst for its Luxembourg office. You will assess internal models used for credit risk scoring, pricing and risk analytics to order to keep the Bank at the forefront of market and regulatory developments in quantitative risk modelling and credit risk assessment.
You will couple technical expertise with strong business judgment to make the right decisions about model development and build a team to solve challenging business problems using advanced statistical methods including AI, ML and quantitative analytics.
Contribute in the design of new algorithms for credit scoring and risk pricing across various business domains
Challenge and enhance the existing ML algorithms for credit scoring and pricing
Ensure models are fit for purpose through development of model performance monitoring (via accuracy metrics, business KPIs, etc.) and recalibrate or redevelop these models when necessary
Establish model validation framework (e.g. predictive analytics, data analysis, back-testing, outcome analysis)
Apply best practices for model change management and deployment into Bank's infrastructure
Partner with Data Scientists/Engineers to implement new ideas and algorithms in the business value chain
Establish solid data governance framework and responsibilities for data ownership across involved departments
Support development of analytical tools for the Risk department
Support integration of new models and products into the Bank's infrastructure and on-going enhancements
Skills and Competencies
At least 8 years of relevant experience in a similar role preferably in the Fintech industry
Statistical modelling expertise e.g. classification techniques, XGBoost and know-how in predictive analytics tools
Solid programming skills e.g. Python, R and strong proficiency in database technologies e.g. SQL
Hands-on experience in applying ML techniques to solve real business problems
Business acumen and understanding value levers within the business that can be targeted by ML algorithms
Highly numerate background with an advanced degree in an analytical discipline (e.g. Mathematics, Computer Science, Physics, Statistics) and a deep understanding of statistical methods and machine learning algorithms
Strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices
Knowledge of financial and banking instruments, where experience in digital lending would be advantageous