Datonomy Solutions is founded on a business model called Connected Value Creation – this enables us to add value to all key stakeholders and unlock true growth, collaboratively. We believe in doing well by doing good, and the work we do creates value for employees, customers, society and the environment.
Building a career with Datonomy allows you to work on projects that interest you, and with the tech stack that appeals to you most. Diverse teams comprising a variety of cultures, ages and backgrounds are proven to be more effective – this also ensures that teams don’t become rigid and change-averse.
We are looking for 3 juniors (junior with <4 years of experience.) and 1 senior ( experienced hire having> 7 years)
Our ideal candidate is working with an outperforming drive and has an analysing and problem-solving mentality.
- Developing models used in the domain of credit risk, asset risk, operational risk and other risk domains;
- Developing models in line with model governance policy and regulatory guidelines;
- Managing the model development projects and ensuring delivery of the model within the agreed timelines and quality;
- Collecting, verifying and if needed cleaning data;
- Testing the quality of the developed models and recalibrating if needed.
- Analyse the model performance and advise on model quality/accuracy;
- Analysing data in order detect portfolio trends which cause significant changes in the capital or are not within the risk appetite.
To succeed in this role, you have the following skills and experience:
- Quantitative academic education in a relevant field, like econometrics, statistics, mathematics or physics;
- Good knowledge of statistics, econometrics, financial mathematics, stochastic calculus and/or machine learning;
- At least 4 years of work experience in credit risk model development in banking environment;
- Project management experience of model development for regulatory models;
- Experience in working with financial regulations, specifically Basel 3 and 4
- Able to effectively communicate about model developments and model impact;
- Experienced in statistical languages (e.g. SAS, R) or modern programming languages (e.g. Python);
- Experience with data analytics, (pre)processing, and data handling is preferred;
- Experience with machine learning/advanced analytics techniques is preferred.