Senior Manager Credit Risk Data Scientist Senior Manager Credit Risk Data Scientist …

Grupo BBVA
in Madrid, Spain
Permanent, Full time
Last application, 19 Jan 21
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Grupo BBVA
in Madrid, Spain
Permanent, Full time
Last application, 19 Jan 21
----------
Posted by:
Ines Fueyo • Recruiter
Posted by:
Ines Fueyo
Recruiter
GRM Analytics is the Discipline, within Global Risk Management, responsible for the development of methodologies and models in the field of risk modelling of the BBVA group. The analysis and use of new data sources and the implementation of new modelling techniques is a core activity within this team.

Our area:

The Global Risk Management (GRM) has a clear strategy aimed at achieving, risk adjusted profitability and recurrent value creation; using a model portfolio approach to manage the group’s activity as a basis for a better capital and a better risk management digitization framework.

GRM Analytics is the Discipline, within Global Risk Management, responsible for the development of methodologies and models in the field of risk modelling of the BBVA group. The analysis and use of new data sources and the implementation of new modelling techniques is a core activity within this team.

About the role, what you should know: 

Based in Madrid, the successful candidate will join the Advanced Analytics COE (Center of Expertise) of  Global Risk Management Holding Area  and will assume hands-on leadership responsibility  in design and development of quantitative risk analytics according to BBVA Strategy.

This is a great opportunity for a hands-on talent ready to take on the next level of challenge to broaden expertise in Risk Modelling, develop leadership and communication skills

The main purpose of the role is to lead the design, deliver and continually update industry-leading credit risk models (such as rating/scoring, IFRS9, IRB models and forecasting models), through the following tasks:

  • You will join a team to develop credit risks models in a Big Data platform accordance with internal standards and best banking practices to solve real business needs 
  • You will write code, document models and test cutting edge Big Data technologies
  • You will explore, crunch and visualize real data identifying  promising data sources to extract valuable insights  
  • You will maintain relationships with a broad range of internal divisions within the bank to ensure successful implementation of models and analytical initiatives
  • You will work in a  multicultural environment that will allow you to develop your career in an international context and you will be part of the Data Science Community of BBVA

Qualifications:

  • University degree holder or above in a quantitative discipline such as Mathematics, Statistics, Science or Engineering
  • Master’s degree,  postgraduates or PhD degree or equivalent background in a quantitative discipline. 
  • 8-10 years of experience  in credit risk modeling  with strong hands-on experience in data analytics and quantitative modeling
  • Experience in the development and/or validation of IRB credit exposure methodologies is required
  • Experience with relevant regulatory projects (EBA new DoD, Basel III implementation, IFRS9, etc.)
  • Experience with regulatory relationships with the ECB and national supervisory authorities with regard to model-related topics. 
  • Strong analytical and programming skills. (SQL, Python , R)
  • Strong understanding of credit products and associated risks
  • Experience with Big Data and Machine Learning or deep learning  technologies ( is a plus), 
  • Minimum level of English (C1).

About you:

We are looking for an enthusiastic person, who has the following characteristics:

  • You must be a hands-on quant, a good communicator capable of providing thought leadership with the ability to influence discussions with other senior professionals across the enterprise. 
  • Strong organizational and project management skills to manage different tasks with competing deadlines
  • Exceptional problem-solving skills and strong attention to detail
  • Ability to explain complex topics in a simple and clear manner 
  • Proactivity and autonomy to develop different lines of work
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