Assistant Manager, Risk Modelling, Credit Risk Measurement

Place of work Work from home
Contract type All types
Start date -
Salary -

Job details

Job description, work day and responsibilities

We assist financial institutions across the Model Risk Management lifecycle. The primary objective of our team is to work collaboratively with our financial services industry clients to design, build and implement credit risk models. We advise and support a diverse group of clients on how best to deliver value in the face of a changing and complex regulatory agenda.

Connect to your career at Deloitte

Deloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more.

What brings us all together at Deloitte? It’s how we approach the thousands of decisions we make every day. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, wherever we are in the world, we lead the way, serve with integrity, take care of each other, foster inclusion, and collaborate for measurable impact. These five shared values lead every decision we make and action we take, guiding us to deliver impact how and where it matters most.

Connect to your opportunity

You will work collaboratively with the wider Credit Risk Modelling team and our clients. The role requires flexibility to tackle a wide range of tasks:

Contribute to all aspects of credit risk model development and deployment including design, coding, testing, validation, and review. The most common types of credit risk models worked on by the team are operational scorecards, IRB capital models for Pillar 1 Credit Risk, IFRS 9 impairment models, forecasting models, stress testing models, and climate risk models.
Help deliver projects to evaluate, design and implement policies, procedures, and strategies to effectively deploy and execute credit risk models and processes, consistent with regulatory requirements and/or market practice across credit risk model delivery.
Perform reviews of credit risk model deployment and execution frameworks, including gathering business requirements, assessing conceptual designs, examining governance and controls, and testing outcomes.
Help the team expand its range of services and solutions in the marketplace, considering operations, analytics and target operating model considerations for clients, plus how to deliver with third party providers.
Contribute to credit risk model deployment and implementation teams (potentially including on-shore and off-shore resources), having a broader perspective of potential issues encountered when working with diverse teams and the strategies to overcome them.
Keep up to date with academic, technical and industry developments in the field of credit risk management, deployment, and implementation.
Contribute to developing thought leadership and new and innovative solutions/analytical techniques in credit risk modelling.
Applicants will need to be able to quickly and efficiently review large volumes of information to identify and disseminate the key points in a coherent manner.

Applicants should be committed to building long-term, robust, and professional working relationships with clients and key stakeholders, working with our senior management team to develop industry contacts. Candidates should also share our firm’s commitment to creating and maintaining a respectful and inclusive culture.

Connect to your skills and professional experience

To qualify for the role, essential attributes are:

A numerical degree or equivalent, e.g., Mathematics, Engineering, Physics, Operational Research, Computer Science (a Master’s degree in a relevant quantitative/finance discipline or Professional qualification such as PRMIA, GARP, CFA would be an advantage), or equivalent experience.
Code (the language is not important); or ability to break down an applied maths problem into arithmetic and logical steps.
A strong work ethic and a professional and personable demeanour.
High personal standards with respect to the quality of your own work.
The ability to work effectively as part of a wider team, furthering common goals and working within demanding deadlines.
Additional desirable attributes include:

Financial Services experience, either as part of a Financial Services Institution, in an advisory or business consulting capacity to similar organisations or in the regulation of such institutions, particularly in the following areas: Retail/Commercial/Corporate Banking Credit Risk.
Credit Risk Modelling experience (in one or more of the following PD/LGD/EAD modelling, Basel II & III framework, operational scorecards, IFRS 9 lifetime expected credit loss and stress testing models including time series modelling techniques) for banking book exposures would be a significant benefit.
Experience interpreting regulation, consulting with a variety of stakeholders and building consensus as part of the decision-making process.
Experience of credit risk management and delivery software available in the market, which is used for credit risk management and model execution across the customer lifecycle.
Credit risk management, credit risk modelling or business expertise within a Retail/Commercial or Corporate bank, with the ability to apply technical financial services regulation to practical business scenarios and advise on the strategic business and financial impacts thereof.
Highly motivated, with a proven track record and ability to work on own initiative within a challenging/dynamic work environment.
Interpersonal and influencing skills, including strong oral and written communication of technical concepts to a nontechnical audience.
Strong IT skills including Microsoft applications (e.g., Word, Excel, PowerPoint) and statistical coding applications (e.g., Python, R, SAS).
Company Name: Deloitte
You will be redirected to another website to apply.
Offer ID: #1244338, Published: 3 hours ago, Company registered: 1 month ago

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