Credit Risk Modeling Specialist  

Key Responsibilities

• Support all business functions of the bank in terms of model development, deployment, and implementation
• Identifies metrics and variables that can be used for feature engineering and selection in model development
• Writes queries to extract, aggregate, and transform data to obtain customer level information for model development
• Develops models for the bank, such as but not limited to credit risk models, Alternative Credit Underwriting (ACU) models, propensity models, etc.
• Drives the implementation of models and collaborates with the different business function, such a Risk, Products, Technology, Credit, Collections, in the development and implementation of models
• Designs and creates MIS and dashboards to monitor and track the performance of models and implemented action plans
• Applies Data governance principles and prepares documentations regarding the business model, its specifications, scripts, and data structure
• Writes memos and presents to upper management and/or committees for notification and/or approval
• Manages and facilitates committee discussions, such as the Philippine Modelling Committee
• Recommends policy updates and test programs in accordance with model and loan portfolio performance
• Supports the other members of the Decision Science and Management Team in achieving business objectives and metrics

Qualifications

Master’s in Business Administration, Data Science, Computer Science, Industrial Engineering/Operations research, Mathematics, Statistics, Informatics, or any related field

Relevant Work Experience

• Min. 5 years in a bank or financial institution in developing and managing models
• Min. 3 years doing statistical analysis and recommending policies
• Min. 3 years in MIS/dashboard development
• Min. 3 years in R, python, and/or SAS
• Min. 3 years in SQL, Hive, or any data querying application

Required Competencies and Skills:

• Business Intelligence tools: QlikSense, Tableau, MS Power BI
• Statistical programming: R Programming, Python, SAS
• Business/Domain background: banking, marketing, e-commerce, and finance
• Data engineering background: Big Data Appliance, Hive, Hadoop, Spark, and/or Pig, SQL, NoSQL
• Stakeholder management
• Project management
• Presentation and communication