SR&T Senior Consultant, Financial Risk (Credit Risk Modeler)

• Be part of an engagement advisory team to Develop/Validate/Enhance Credit Risk models (e.g. IFRS 9 ECL Model, Credit Scoring / Scorecard, and Credit Rating) based on industry best practices. You will also be able to learn and work in other quantitative and analytical financial risk areas such as model risk management, business intelligence, machine learning and artificial intelligence.
• Assist in managing / driving the project, team, and client servicing.
• Involve in business development initiatives in the aforementioned areas.

• Actively seek out developmental opportunities for growth, act as strong brand ambassadors for the firm as well as share their knowledge and experience with others.
• Respect the needs of their colleagues and build up cooperative relationships.
• Understand the goals of our internal and external stakeholder to set personal priorities as well as align their teams’ work to achieve the objectives.
• Constantly challenge themselves, collaborate with others to deliver on tasks and take accountability for the results.
• Build productive relationships and communicate effectively in order to positively influence teams and other stakeholders.
• Offer insights based on a solid understanding of what makes Deloitte successful.
• Project integrity and confidence while motivating others through team collaboration as well as recognising individual strengths, differences, and contributions.
• Understand disruptive trends and promote potential opportunities for improvement.

• 4-8 years of relevant experience spent within a credit risk model development or model validation team at major banks / financial institutions or consulting firms.
• Solid academic background with a Degree in Statistics, Data Science / AI, Financial Engineering, Quantitative Finance, or other relevant post graduate degree.
• Solid knowledge of common practices in credit risk models, including IFRS 9 expected credit losses (PD, LGD, EAD) and credit scoring / scorecard (Application, Behavioural, Credit Rating) methodologies.
• Solid knowledge of supervisory/regulatory requirements as it pertains to credit risk models, including IFRS 9 ECL and Basel.
• Foundation knowledge in statistics and machine learning (e.g. Classification, Regression, Clustering, Hypothesis testing).
• Hands-on data processing, reporting/visualization and modelling skill in pertinent languages such as Python, R, SAS, and Excel(VBA).
• Strong critical thinking and analytical problem-solving abilities.
• Ability to communicate complex quantitative analysis in a clear, precise manner.
• Proficiency in English & Thai
• For male, Certificate of Military Exemption is a must