Quantitative Analyst FRTB (VP) Quantitative Analyst FRTB (VP) …

Barclays UK
in London, England, United Kingdom
Permanent, Full time
Last application, 23 Sep 19
Negotiable
Barclays UK
in London, England, United Kingdom
Permanent, Full time
Last application, 23 Sep 19
Negotiable
The role requires a superior developer, with experience in C++ and Python, to facilitate the efficient development of our models library, and of our capital replication infrastructure and what-if tools. This includes prototyping, production implementation, testing, maintenance, and support; it requires understanding of large datasets, risk models, tail statistics, and computational performance.

About Quantitative Analytics

The Quantitative Analytics group is responsible for the research, development and implementation of market leading quantitative models across all asset classes and areas (Interest Rates, Inflation, Credit, Equity, Foreign Exchange, Commodities, Emerging Markets, Market Risk, Counterparty Credit Risk, Banking Book, Asset and Liability Management and Financial Modelling).

About QA Market Risk The role is in the global Quantitative Analytics (QA) function, working in the Market Risk (MR) team. QA MR is responsible for the research, development, and documentation of the regulatory capital models for market-risk RWAs. The team is part of the QA Trading Book Risk (TBR) group in the investment bank.

We are an equal opportunity employer and we are opposed to discrimination on any grounds."

Overall purpose of role

The role requires a superior developer, with experience in C++ and Python, to facilitate the efficient development of our models library, and of our capital replication infrastructure and what-if tools. This includes prototyping, production implementation, testing, maintenance, and support; it requires understanding of large datasets, risk models, tail statistics, and computational performance.

Key Accountabilities

  • Maintenance of current risk applications and models
  • Come up with clear and solid designs to implement proposed modelling changes, to deliver in dynamic, agile, and often ambiguous contexts
  • Deliver prototypes using or extending as appropriate our Python-based modelling platform
  • Develop the models in C++/Python/R and assist IT to integrate them into the production system.
  • Participate to the design and the development of a robust, scalable, and extendible Market Risk solutions and their integration into the Risk engines framework.
  • Support Risk, FO and IT users of our analytics

Stakeholder Management and Leadership

Candidates must be able to, and to communicate effectively with stakeholders (Risk IT, Project Managers, Model Validation, Risk Managers) and colleagues in QA. .

Strong communication skills, including to non-technical audiences are essential

Risk and Control Objective [This section is mandatory for all role profiles and must not be deleted]

Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays Policies and Policy Standards.

Person Specification

A successful candidate must be proactive and detail-oriented, yet adaptable to changing requirements and flexible at the same time.

The candidate will be expected to show high level of initiative, motivation and drive; ability to work independently and to influence progress

Essential Skills/Basic Qualifications:

  • Familiarity with market risk models (ideally with VaR) or pricing models.
  • Familiarity with and experience in the implementation of the FRTB Framework
  • Python/R/C++ hands on development. Should include scientific stack (numpy pandas, scipy etc…), multi-processing, caching, and handling complexity
  • Quantitative & statistical skills, knowledge of financial concepts & products
  • Organized, with great attention to detail; strategic thinker, capable to deliver on time

Desirable skills/Preferred Qualifications:

  • Strong development experience: data structures, software architecture, algorithms
  • Programming experience in shared codebase: source control, unit testing, continuous integration
  • Scenario generation, Monte Carlo and/or historical simulation methods
  • Experience working with large data sets and working around data quality issues
  • SQL or other modern query language (e.g. MongoDB)
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