Job Title: EY- Assurance –Manager- FAAS – IT

As part of our EY-Assurance Team, the Manager will be responsible for working closely with FAAS Senior Managers and leadership on clients and engagements across Americas and EMEIA to provide end to end digital solutions to enable the new accounting standards/Financial RISK.

The opportunity

We’re looking for incumbents who is responsible for the timeliness and quality of the work as per Project requirements for our FAAS team and possess strong technical and domain knowledge under IFRS/Financial RISK. The role requires prior experience and knowledge of IT consulting, with strong expertise in IFRS9 ECL, credit risk modelling and AI-enabled digital risk solutions.

Your key responsibilities

• Accountable for strategic risk solutioning, driving adoption of advanced analytics and AI within regulatory risk frameworks
• Support business development and proposal creation, including solution design, effort estimation and value articulation
• Demonstrate deep technical capabilities and industry knowledge of financial products
• Lead components of large-scale client engagements and/or smaller client engagements while consistently delivering quality client services
• Understand market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business
• Oversea automation of ECL calculations, monitoring, and disclosures, driving efficiency and audit readiness
• Support leadership to collaborate between clients, risk teams, IT and data engineering, translating regulatory requirements into scalable solutions
• Lead regulatory, audit, and model governance interactions, including committee presentations and technical walkthroughs
• Guide teams on IFRS 9 interpretation, documentation standards, and regulatory expectations
• Manage onshore–offshore delivery models, ensuring quality, timelines, and stakeholder alignment
• Contribute to risk transformation roadmaps, digital strategy proposals, and client advisory initiatives
• Support the development and management of the relationships with external and internal (EY) clients

Skills and attributes for success

• End-to-end ownership of digital risk engagements, combining IFRS 9 expertise with scalable, technology-driven solutions
• Strong technical leadership in credit risk modelling (PD, LGD, EAD), challenger frameworks, and model risk governance
• Solution-architecture mindset, driving automation, AI-enabled analytics, and sustainable risk platforms
• Trusted client advisor, effectively translating complex regulatory and technical concepts for senior stakeholders, auditors, and regulators
• Delivery-focused leader, managing cross-functional teams, resolving risks proactively, and ensuring quality, timeliness, and compliance

To qualify for the role, you must have

• Deep hands-on expertise in IFRS 9 ECL solutioning, including end-to-end design, calibration, and implementation of PD, LGD, and EAD models across banking portfolios
• Strong command of credit risk modelling and validation techniques, including feature engineering, back-testing, sensitivity analysis, challenger model development, and performance monitoring
• Advanced technical capability in Python, R, SPARK, HDFS, Dot Net, PostgreSQL and SQL to build scalable risk data pipelines, ECL automation, and AI\ML enabled Risk solutions
• Solid grounding in credit risk, model risk management, and regulatory governance, with experience supporting audits, model reviews, regulatory interactions and Loan & Core Banking Integrationse

Qualifications, Certifications and Education – Must-have

• Postgraduate (master’s in finance, Information technology or a related field) with at least 13-15 years of related work experience
• Complete, end-to-end understanding of credit risk model development, validation and implementation for the banking book portfolio.
• Knowledge of Credit Risk and Risk Analytics techniques is desirable.
• Machine Learning models and its applications.
• TOGAF certification is desirable.

Ideally, you’ll also have

• Machine learning exposure
• Experience with banking clients
• Experience in enterprise architecture frameworks
• Proficiency in MS – Excel, MS – Office.
• Knowledge on any Data analytics/visualisation tools will be additional advantage.
• Strong communication, Interpersonal, Analytical Skills & highly proactive in approach