BNP Paribas is a leading European bank with an international reach. It has a presence in 73 countries, with more than 192,000 employees – including more than 146,000 in Europe and over 4,000 in Portugal alone.
BNP Paribas is present in Portugal since 1985, having been one of the first foreign banks to operate in the country. Today, BNP Paribas has several entities operating directly in this territory, offering a wide range of integrated financial solutions to support its clients and their businesses.
Worldwide, the Group has key positions in its three main activities: Domestic Markets and International Financial Services (whose retail-banking networks and financial services are covered by Retail Banking & Services) and Corporate & Institutional Banking, which serves two client franchises: corporate clients and institutional investors. The Group helps all its clients (individuals, community associations, entrepreneurs, SMEs, corporate and institutional clients) to realise their projects through solutions spanning financing, investment, savings and protection insurance.
The team named STFS, for Stress Testing and Financial Synthesis, coordinates the strengthening of BNP Paribas’ Stress-Testing (S/T) and planning capabilities so as to better serve Business Lines, Legal Entities and Group needs and meet supervisory requirement on these matters, and in a cost-efficient manner.
To that effect, STFS aims at building a flexible, industrialized, central utility accessible by BNP Paribas’ Business Lines and Entities (B/E) for their local needs and their contribution to Group exercises. STFS offers an integrated S/T service to B/Es to support them in capitalizing on the shared framework for their local needs.
Within the STFS platform, Stress-Testing Methodologies & Models (STMM) is responsible for the S/T models and methodologies for all major drivers impacting P&L, liquidity and capital planning globally for the Bank. The team is also responsible for coordinating the development and implementation of models and methodologies that combine different risks (e.g. market risk, operational risk, credit risk, liquidity risk…). It ensures the consistency and robustness of S/T models and methodologies by developing models as a transversal expertise center for the Group liaising with the different topics experts in RISK. The team is composed of quantitative analysts and data scientists with a clear orientation towards innovation. Its transversal positioning also brings the opportunity to work with stakeholders in many regions and get an understanding of a variety of business of the bank.
Within STMM, one team is dedicated to credit risk. This team covers the models and methodologies used for the projection of credit risk parameters for stress testing and IFRS 9. The team expertise’s is related to:
- Quantitative analysis: portfolio modelling, rating migration and LGD models
- Time series modelling for the anticipation of risk parameters
- Numerical treatments
- Reporting and analysis of stress testing outcomes
ROLE AND RESPONSIBILITIES
The STMM team in Lisbon is dedicated to credit and works in a one-team manner with the credit team based in Paris. This team is looking for data scientists/analysts with the following areas of expertise:
- Carrying out stress test exercise for internal and Regulatory purposes: stress test exercises are relying on macroeconomic parameter forecasts. These parameters have impacts on forecasted default rates and credit risk cycle. You will be in charge of calculating and computing these parameters and then feeding the stress test engine.
- Analyzing and producing automatic reporting for quarterly stress test exercise and provide stress test results for local regulators.
- Carrying out IFRS9 quarterly exercise: updating IFRS9 parameters according to macroeconomic scenario, ensuring consistency between stress test and IFRS9’s models, sensitivity analysis, rationalization effect measurement,...
- Data science: treatment of large dataset in a big data environment, using Python/R code. Data analysis and treatment on both input parameters (including loan and client level portfolio data) and on model generated data.
To be successful in this role, the candidate should meet the following requirements:
- Junior (0-3 years experiences - willingness to consider recent graduates) with strong desire to learn
- Strong academic background, with at minimum a Master degree in mathematics, econometrics or statistics
- Background in programming with ability to use at least two of the following tools: Python, R, VBA
- Knowledge of credit risk management principles and BCBS regulations
- Understanding of Management control principles would be appreciated
- Languages: English
In addition, the candidate should have the following essential behavioural skills:
- Creativity & Innovation skills
- Be a problem solver and result oriented
- Autonomy & Adaptability
- Reliability and sense of precision
- This role will expose the candidate to a wide range of professionals within the bank. Therefore, communication skills, both written and verbal, play an essential part in the day-to-day role
The candidate should be available for periodic training abroad (short term in Paris).
BNP Paribas is an equal opportunity employer and proud to provide equal employment opportunity to all job seekers. We are actively committed to ensuring that no individual is discriminated against on the grounds of age, disability, gender reassignment, marriage or civil partnership status, pregnancy and maternity, race, religion or belief, sex or sexual orientation. Equity and diversity are at the core of our recruitment policy because we believe that they foster creativity and efficiency, which in turn increase performance and productivity. We strive to reflect the society we live in, while keeping with the image of our clients.
Please note that only applications submitted in English will be considered.
In case you are selected for this role, further documentation will be requested to support your hiring process.