Model Risk Analyst (Hybrid)

at  BNP Paribas

BNP Paribas is a leading bank in Europe with an international reach. It has a presence in 73 countries, with more than 196,000 employees, including around 149,000 in Europe. The Group has key positions in its three main activities: Domestic Markets, 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.
BNP Paribas Corporate and Institutional Banking is a globally recognized leader offering capital markets, securities services, financing, treasury and advisory solutions.

REQUIRED HARD SKILLS:

Strong quantitative background, owning an MSc or PhD degree in a quantitative subject, preferably a degree in financial mathematics.
This position requires proven professional experience in alignment with the responsibilities.
Advanced knowledge of capital markets: how the markets operate, what the key products are, what the main risk drivers are, and risk neutral valuation of the financial instruments and derivatives.
Familiarity with pricing models as well as with market and/or counterparty risk modelling techniques.
Strong understanding of stochastic processes and derivatives pricing techniques, familiarity with several underlying asset price models and with various numerical techniques.
Advanced programming skills in C++ / C# or other languages allowing fast assessment of model features and carrying out comparison of model alternatives.
Experience with model validation techniques and model risk management processes.

REQUIRED SOFT SKILLS:

Strong curiosity of the field, proactively seeking opportunity of learning and progress, and staying up-to-date with the newest developments in the field.
Being at ease with building relationships with people outside of the immediate team and seeking to understand diverse perspectives.
Ability to engage stakeholders and obtain the required information without power of authority.
Ability to challenge the proposed methodologies and to provide alternative solutions.
Validation skills to valorise new ideas, both supportive and critical, and to examine problems from several different points of view.
Specific audit mind-set and skills to review methodologies that are regulation-driven.
Result orientation, managing the time efficiently focusing on the mission and providing the highest quality work and precision under the constraint of given resources.
Eagerness to take ownership of projects and be autonomous in finding out the next steps.
Genuine sense of care and respect for people, acting as a team player and proactively supporting colleagues.
Good communication skills in English to convey clearly ideas in front of various audiences, and concise writing skills.

PURPOSE & SCOPE OF ROLE:

The Model Risk Quantitative Analyst position covers the team members who have already gained sufficient model validation experience to be fully autonomous in carrying out model reviews and to coach entry-level team members for the execution of their reviews and/or who can initiate and put through enhancements to the team’s operation.
Model Risk Quantitative Analysts work mostly on independent reviews interacting with the validation managers and with the auditees. The latter usually includes model developers, teams operating the models, and model users. Those stakeholders may be within RISK, within the Business, or within other Group functions.
The scope of the role is global, covering the model risk management of methodologies in scope globally within the Group.

KEY RESPONSIBILITIES OF ROLE:

Appropriate the work plan and review strategy as defined by the validation manager.
Analyse and opine on model risk by performing quantitative and qualitative reviews of the selected models.
Issue reports and recommendations and advise stakeholders about the conceptual soundness, sound implementation and sound operation of the investigated models.
Manage allocated review projects / activities and deliver timely and efficiently.
Coach entry-level model risk quantitative analysts.
Proactively take initiatives for internal projects to enhance the team’s operation.