Quantitative Analytics Manager

We are offering an opportunity for a Quantitative Analytics Manager to join our team located in Hartford County, Connecticut. The role involves working in the financial industry, focusing on quantitative models and other analytic tools, with a significant emphasis on credit risk and capital management modeling.

Responsibilities:

• Develop and document quantitative models and other analytic tools, with a particular focus on credit risk and capital management modeling.
• Use advanced analytics tools like AI and ML in the risk management and analytics processes, and ensure their responsible implementation.
• Communicate complex modeling concepts to both technical and non-technical audiences in a clear and concise manner.
• Collaborate with cross-functional teams, including risk management, finance, and business operations, to align and integrate quantitative modeling initiatives with business strategies and objectives.
• Identify analytics use cases and opportunities for applying quantitative modeling techniques to address business challenges and opportunities.
• Conduct thorough analysis and evaluation to prioritize use cases based on their potential impact on business outcomes.
• Provide guidance and support to business stakeholders in interpreting and leveraging model outputs to inform decision-making processes.
• Collaborate with the data team to outline data requirements, ensure governance and data quality around key fields, and to build data pipelines for production models.
• Document model development and testing in accordance with Model Risk Management guidelines.
• Oversee the implementation of models into operational systems and processes, ensuring seamless integration and functionality.
• Work closely with IT and data teams to ensure efficient deployment and maintenance of models in production environments.
• Proficiency in Quantitative Analytics is required.
• Must have a strong command of R Programming.
• Familiarity with Databricks is necessary.
• Must have experience with Credit Risk Models.
• Knowledge of Stress Testing is mandatory.
• Experience with GitHub is essential.
• Should have a background in Artificial Intelligence (AI).
• Proficiency in Machine Learning is necessary.
• Familiarity with Model Validation is required.
• Ability to provide leadership to a team is important.