Risk Analytics Head

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; escalate 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)