General Information

Position
Risk Quantitative Analyst
Work arrangement
Full-time
City
Bucharest
Country
Romania
Department
Risk Advisory
Team
Financial Industry Risk & Regulatory
Area of interest
Consulting
Way of work
Hybrid

Description & Requirements

Who we are looking for
  • Minimum 1 year relevant experience working in a financial institution or in a related field in a relevant risk or quantitative position such as: credit risk, financial supervision, market risk or financial modelling;
  • Strong academic background, including a degree in Data Science, Business Analytics, Statistics, Mathematics, Engineering, Computer Science, or other related field with strong quantitative focus;
  • Master’s degree in a quantitative discipline is preferred but not mandatory;
  • Good knowledge of programming, e.g. SAS, R, Python, SQL,VBA, knowledge of Access, Microsoft Excel;
  • Experience in data modelling and management, integration and manipulation of large datasets is an advantage;
  • Familiarity with the mathematical methods used in credit risk modelling is an advantage;
  • Familiarity with the prudential regulatory requirements and/or IFRS 9 is an advantage;
  • Strong multi-tasking and project management skills;
  • Excellent English written and oral communication skills;
Your future role
The successful candidates will work alongside other subject matter experts in the FSI Risk and regulatory department and will be part of an international team with substantial knowledge of laws and regulations in accounting, risk and advisory as well as best practices in banking supervision.

Key Responsibilities:
  • Review and validation of credit risk internal models;
  • Support the design, calibration, and implementation of models;
  • Document models, methodologies, analyses, and findings;
  • Assess the quality of data underlying risk models and model calibration;
  • Engage with key client representatives to obtain an understanding of risk practices and assess them;
  • Provide support to clients in the areas of internal governance, policies and frameworks in place linked to quantitative risk management;
  • Interpret new regulatory requirements focusing on those specific to internal models;