Join us as a Quantitative Modeler- -Assistant Vice President in Quantitative Analytics (QA) team at Barclays. QA is responsible for developing, testing, implementing, and supporting quantitative models for valuation and risk management of traded assets, regulatory and economic capital, impairments, asset-liability management, operational risk, and stress testing across Barclays.

Overall purpose of role

The Quantitative Modeler position involves building targeted solutions that integrate effectively into existing systems and processes while delivering strong and consistent performance. Working with QA Managers, the quantitative modeler role provides expertise in project design, predictive model development, validation, monitoring, tracking, implementation and/or specification

Key Accountabilities

• Develop predictive models, statistical analyses, optimization procedures, monitoring processes, data quality analyses, and score implementations and specifications with high levels of accuracy and use of cutting-edge techniques to develop best in class models.
• Participate in overall project design and delivery with Quantitative Analytics other functional teams and end-clients.
• Produce robust documentation to ensure replicability of results and fulfil Barclays governance requirements.
• Work with other colleagues to ensure project completion within agreed time frames and end-client satisfaction.
• Contribute to the broader Quantitative Analytics department through participation in peer reviews, terms of reference reviews, modelling forums, and ad hoc project collaboration.

Stakeholder Management and Leadership

• Good communication skills with an ability to present in technical committees.
• Understand business requirements, validate, clarify and where appropriate, challenge/refine them with the stakeholder, to translate them into a meaningful functional specification on which to base build activity.
• The role holder will be expected to hold code and document walkthroughs with peers and senior managers who will provide appropriate challenge to drive quality.

Decision-making and Problem Solving

• Impact analysis of existing managed solutions in response to bank wide initiatives (such as operational system changes).
• Spot and take advantage of opportunities to improve code efficiency, data transformation, space utilization.
• Rapid model implementation data exploration and extraction to source the most suitable data items to support the model build validation exercises.
• Role holder will inform the strategic direction of the Python environment, the principles applied and the toolset evolution.

Person Specification

• Strong communication to different senior stakeholders, both written and verbal, will be a key competency of the successful candidate.
• This needs to be coupled with strong attention to detail, a rigorous and methodical approach to maintain clear and concise governance, and ensuring timely delivery.
• A motivated, disciplined, self-starter profile is preferred.  Someone who is confident in their own ability/skills, such that they can make recommendations and take decisions, after considering all the factors
• The candidate should be able to work in isolation and within a team environment, as required.

Essential Skills/Basic Qualifications:

• Minimum Bachelors Degree in quantitative discipline (e.g. Finance, Mathematics/Statistics or Economics).
• Hands-on experience in statistical model development and basic knowledge of Capital and impairment concepts.
• A good knowledge of data analysis, theory and statistical techniques (such as linear or nonlinear models, logistic regression, macroeconomic forecast, decision trees, cluster analysis and neural networks etc.)
• Proficiency in with analytical software Python, SQL tools (e.g., Oracle), Unix platforms, and MS Office required. 
• Model implementation using DevOps tools like TeamCity, Jira, BitBucket and Nexus etc.
• Project and stakeholder management.
• Experience in financial institution data, supporting model development, implementation and productionisation within credit wholesale, consumer, finance or treasury.

Desirable skills/Preferred Qualifications:

• Masters degree in Computer Science, Math, Statistics or Economics
• Knowledge of Big Data platforms such as HADOOP and its eco-system
• Knowledge of credit card and/or banking retail business (specifically Mortgage and Unsecured) is strongly preferred
• Good exposure to statistical model development - familiarity with Consumer or Wholesale Credit risk modelling experience.
• Supported or working on stress testing across Risk, Treasury or Finance
• Data science and Machine learning background
• Experience working within quantitative analytics team delivering models
• An understanding of the fundamental principles of the Basel and / or of IFRS 9 standards

You may be assessed on the key critical skills relevant for success in role, such as experience with statistical model development, python programming, , as well as job-specific skillsets.

The role is based out of Noida.

Purpose of the role

To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making

Accountabilities

• Design analytics and modelling solutions to complex business problems using domain expertise.
• Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
• Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
• Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
• Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
• Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
• Ensure all development activities are undertaken within the defined control environment.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L Listen and be authentic, E Energise and inspire, A Align across the enterprise, D Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge and Drive the operating manual for how we behave.