Risk Analytics Head

City Savings Bank, Inc.; Pasig; On-site; PHP 1,500,000 - 2,300,000; Full time

Job summary

City Savings Bank, Inc. is seeking a Risk Analytics Head in Pasig, Philippines to lead advanced analytics and modeling initiatives across multiple risk types.

The role focuses on developing, validating, and enhancing scoring models, and laying out ML Ops pipelines for rapid rollout and automated monitoring of models. The successful candidate will work with the CRO and technology teams to deliver data-driven insights, improve risk-based decision making, and drive business performance through

Qualifications

• 5-8 years in business analytics or risk analytics (preferred)
• Experience developing and validating risk models
• Ability to design dashboards and present to stakeholders

Responsibilities

• Develop, validate, and enhance risk scoring models across market, credit, and operational risk
• Build and operationalize ML/AI driven analytics and ML Ops pipelines
• Collaborate with CRO and tech teams to improve risk-based decisions and monitoring
• Automate data extraction, preprocessing, and model evaluation tasks
• Prepare formal statistical documentation and communicate findings to non-technical audiences

Skills

Advanced analytics

ML/AI techniques

Statistical modeling

Data mining

Cross-functional communication

Job description

As the Risk Analytics Head is a key role in the risk organization responsible for advanced analytics and modeling initiatives within City Savings Bank. She/ He will be responsible for developing and enhancing score models across multiple risk areas using traditional methods as well as new AI/ML techniques. Working with the tech team she/he will lay out the ML Ops pipelines and structure for rapid rollout and automated monitoring of models.

Job Specifications:

• Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational.
• Develop, validate and strategize uses of scoring models and scoring model related policies.
• Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations
• Build the foundation of state-of-the-art scientific and technical capabilities within the Data Science department in order to support several planned and ongoing data-analytics projects.
• Provide forward-thinking recommendations to risk management by building in-depth understanding of the domain and available business data assets, especially those pertaining to credit, fraud, collections, operational, market and liquidity risk
• Execute ad-hoc data mining and exploratory statistics tasks on large data-sets related to the business 'strategies.
• Generate actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and data mining
• Collaborate with the CRO to communicate obstacles and findings to relevant stakeholders in an effort to improve risk-based decision making and drive business performance.
• Conducts statistical analysis for risk related projects and data modeling/validation.
• Prepares statistical and non-statistical data exploration, validate data, identify data quality issues.
• Conducts data analysis, data mining, read and create formal statistical documentation, reports and work with Technology to address issues.
• Analyzes and interprets data reports, make recommendations addressing business needs.
• Uses Predictive modeling methods, Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary.
• Generates statistical models to improve methods of obtaining and evaluating quantitative and qualitative data and identify relationships and trends in data and factors affecting research results.
• Validates assumptions; escalates identified risks and sensitive areas in methodology and process.
• Automates data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations.

Qualifications:

• At least 5 - 8 years total working experience in the business analytics or risk analytics domain (preferred)