Quantitative Risk Analyst

Position Summary :

Join a team focused on the success of our customers, the success of our communities, and the success of each other. Farm Credit East (FCE) is the leading provider of loans and farm advisory services to farm, forest product, fishing, and other agricultural business owners across the northeast with $11.

5 billion in total loan volume to 18,000 customers across our 8-state territory. We are One Team Working Together with a focus on our five pillars : Outstanding Customer and Employee Experience, Quality Growth, Operational Excellence, Commitment to our Communities, and Protecting Customer Information.

The Quantitative Risk Analyst will be a key contributor to Farm Credit East's risk modeling, forecasting, and decision modeling efforts.

The successful candidate will utilize quantitative and qualitative modeling techniques, statistical analyses, and various analytics tools to provide actionable information to aid in decision making.

The value drivers for this role are as follows :

• Develops and maintains robust risk models and forecasts that provide insights and enable the Executive Leadership Team and Board to make well-informed decisions..
• Partners with business lines to leverage data and analytics to provide insights, drive growth, enhance profitability, and optimize business processes.

We offer generous benefits including : a 6% 401K match plus an additional defined contribution retirement plan, medical, dental, HSA, paid annual holiday and sick leave, FSA, life insurance, and a bonus incentive program.

Farm Credit East provides all team members with the training and resources needed to be successful in their careers. Technical training, soft skill training, and ongoing professional development provided by Farm Credit East will help you be poised for continued career growth within our organization.

We use state of the art technology for customer relations (Salesforce), internal communication (Microsoft TEAMS) and delivery of services.

Come join a collaborative, customer-focused team at Farm Credit East!

Duties and Responsibilities :

Modeling and Forcasting

• Partnering with Finance and Credit, develop, document, and support the deployment of quantitative models and other analytic tools, focused primarily on credit risk and capital management modeling (expected credit losses, stress testing, economic capital) and automated credit decision models.
• Evaluate and implement AI and ML techniques in the risk management and analytics processes, evaluating potential applications and ensuring responsible implementation.
• Communicate complex modeling concepts clearly and concisely to both technical and non-technical audiences.
• Work across business lines to develop and execute analytics use cases that will drive operational excellence, generate growth opportunities, and / or enhance the customer and employee experience.

Cross Functional Collaboration

• Collaborate with cross-functional teams, including risk management, finance, and business operations, to drive alignment and integration of quantitative modeling initiatives with business strategies and objectives.
• Collaborate with business units to identify analytics use cases and opportunities for applying quantitative modeling techniques to address business challenges and opportunities.
• Provide guidance and support to business stakeholders in interpreting and leveraging model outputs to inform decision-making processes.
• Work collaboratively with the data team to outline data requirements, ensure governance and data quality around key fields, and to build data pipelines for production models.

Model Development Lifecycle

• Document model development and testing in accordance with Model Risk Management guidelines.
• Support model development during internal and / or external model validations and audits.
• Collaborate on 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.
• Develop and implement sound change controls around production models and develop appropriate model monitoring metrics

Job Qualifications and Requirements :

• Bachelor's degree in a quantitative field such as Mathematics, Statistics, Economics, Finance, or related discipline. Advanced degree (Master’s or PhD), while not required, will be looked upon favorably
• 3 + years of experience in quantitative modeling, risk analytics, data science or related field, with a strong background in credit risk modeling, CECL, and stress testing.
• Prior experience in a leadership or managerial role, with demonstrated ability to lead and manage a team of analysts effectively.
• Proficiency in programming languages such as R, Python, or SAS, and experience with AI and ML techniques for predictive modeling and data analysis.
• Salary range : $75,000-$125,000 commensurate with experience.
• We offer hybrid work options after six months of employment with Farm Credit East. Hybrid work options are determined based on job role and balancing the needs of the customers, the team, and individual work performance.

This will be reviewed based on manager discretion.

Farm Credit East is an Equal Opportunity Employer. As an Equal Opportunity Employer, we do not discriminate on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, marital status, parental status, political affiliation, disability status, protected veteran status, genetic information or any other status protected by federal, state or local law.

It is our goal to make employment decisions that further the principle of equal employment opportunity by utilizing objective standards based upon an individual's qualifications for a specific job opening.

In compliance with the Americans with Disabilities Act ( ADA ), if you have a disability and would like a reasonable accommodation in order to apply for a position with Farm Credit East, please call 1-800-562-2235 or e-mail [email protected] .