Financial Credit Risk Modeler

What youll do:

• Develop and validate credit risk models 
• Enhance the usage of Artificial Intelligence / ML and transform into more efficient solutions. 
• Using GCP, SAS, R, Python, for model building and model validation 
• Continual enhancement of statistical techniques and their applications in solving business objectives 
• Compile and analyze the results from modeling output and translate into actionable insights 
• Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process 
• Collaborate, Support, Advise and Guide in development of the models 
• Acquire and share deep knowledge of data utilized by the team and its business partners 
• Participate in global conference calls and meetings as needed and manage multiple customer interfaces 
• Execute analytics special studies and ad hoc analyses 
• Evaluate new tools and technologies to improve analytical processes
• Set own priorities and timelines to accomplish projects (accountability for project deliverables) 
• User-Centric Collaboration: Work closely with analytical modelers to deeply understand their daily bottlenecks, data prep challenges, and coding workflows, translating those difficulties into effective AI solutions.
• Security & Governance: Ensure all internal AI tools adhere to our clients strict data privacy, security, and compliance standards, implementing guardrails for internal data usage.

What youll need:

• Masters in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field.
• Good understanding of Probability of Default (PD), LGD and EAD modeling technique. 
• Proven hand-on experience in Artificial Intelligence and extensive experience in GCP . 
• Very good understanding of Predictive modeling techniques and their application. 
• Knowledge of Credit life cycle 
• Statistics and machine learning techniques. 
• Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis 
• Team player and collaboration skills. 
• Programming skills in GCP, R, SAS, and PYTHON. 
• Fluency with Excel, PowerPoint and Word 
• Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly
• Experience with developing and implementing cloud based analytical soluions in GCP or similar set up. 

Future-Ready Skills (Nice to Have):

• Previous exposure to the Banking, Financial Services, or Credit Analytics industries.
• Familiarity with SAS to aid in building code-translation or modernization tools for modelers.
• Experience in integrated marketing, digital agency, marketing services, or consulting environments preferred.