As a global leader in assurance, tax, transaction and consulting services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime.

 

The opportunity

Within EY's Assurance service line, Financial Accounting Advisory Services (FAAS) professionals provide advisory services encompassing accounting and regulatory support on accounting change and special matters; accounting processes and controls support; GAAP conversion and implementation; on call financial reporting advice; and transaction accounting and financial reporting assistance.

 

Your key responsibilities:

Collaborate with the Senior Manager and the Partner to execute a FAAS strategy that satisfies high client expectations, support the planning, execution and delivery of the engagements Contribute actively in the FAAS engagement team to understand and respond to the client's needs and expectations and develop a client-focused, clear, accurate and well-presented work product Ensure work is delivered in a timely manner and in compliance with EY high standard requirements Work with other service lines and subject matter experts in providing an integrated service delivery across functions in an international team to meet the client high expectations. Identify and communicate relevant trends, developments and key performance drivers relevant to the client and its industry. Assist in developing new opportunities related to new FAAS projects and relationships.

 

Skills And Attributes for Success

Strong analytical, problem solving and critical thinking skills Willingness to learn and continuously expand technical and business skills Ability to understand, produce and communicate complex/technical ideas to a non-technical audience Strong communication, presentation and writing skills in English and Greek. Knowledge of additional languages will be considered an asset Excellent interpersonal skills and ability to work effectively within a team Solid project management skills Team management skills Willingness and ability to travel and work abroad for international projects

To qualify for the role, you must have

Excellent academic background, including a Bachelor and a Master’s in Mathematics, Statistics, , Financial Engineering, Financial Mathematics, Actuarial Science, Operational Research, Econometrics, Data Science, Economics, Finance, Risk Management or other related field with strong quantitative focus. Ph.D. will be considered an asset. A professional qualification in PRM, FRM, ERM, CQF, Actuarial Qualification or progression towards attainment of the same. At least 3-5 years’ experience in risk management

 

Professional experience with focus on one or more of the following:

Quantitative techniques and analytics in various areas within credit risk Model development, validation and implementation across credit risk quantification purposes (i.e. PD/LGD/CCF estimation, decision-making, stress testing) Knowledge of credit risk related regulatory requirements (e.g. IFRS 9, IRB, Stress Testing, Early Warning, Climate and ESG risk incorporation in Credit Risk) Knowledge of risk-related regulatory landscape and requirements Basel II/III implementation. Data management, mining, cleansing and visualization with application on credit risk data Strong skills in programming and quantitative analysis packages (e.g., Python, R, SAS, SPSS) or/and data management (e.g., SQL) Credit policies and processes, credit risk data and related financial institutions’ internal and external requirements. Experience in the design and implementation of credit risk model related frameworks (model lifecycle management, development, validation, implementation).

 

Ideally, you’ll also have

Experience in data analysis, data quality, data automation and data management including familiarity with Big Data technologies  Solid understanding of advanced statistical, Artificial Intelligence and Machine Learning techniques for classification, clustering and forecasting and hands-on experience using programming languages such as Python Experience in working on cloud technologies (e.g., MS Azure, Databricks) Experience in the design and implementation of credit risk model related frameworks (model lifecycle management, development, validation, deployment) Understanding of the credit lifecycle and credit processes (origination, approval, monitoring, workout, and collections) Knowledge of climate and other environmental, social and governance risks and their incorporation into credit decisioning and stress testing