Senior Associate, Credit Risk Analytics
Listed on 2026-08-02
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Finance & Banking
Risk Manager/Analyst, Banking Analyst
What You’ll Contribute
The Sr. Associate, Credit Risk Analytics role is a key position within Sallie Mae’s 2nd Line of Defense Credit Risk team. This position is responsible for performing the analytical review of credit risk related to underwriting, portfolio management, and loss mitigation processes. The Sr. Associate role also provides design and monitoring for the credit risk oversight framework including development of credit risk appetite, risk metrics thresholds, and limits.
This position executes analytical techniques to provide insights into portfolio credit quality at segment level and assessment of emerging risks. Additionally, the position will collaborate regularly with business partners and regulators during portfolio exams as part of the credit review and challenge process.
- Risk analytics & reporting Supports 2nd Line of Defense analytical review of credit risk across the entire credit life cycle. Evaluates risk impact of strategy changes, environmental changes, and related layered risk. Provides analytical support, deep diving into emerging credit trends and performing ad-hoc credit reporting. Provides narratives of observations and preparation of presentation materials. Design and develop Power BI dashboards to meet the reporting needs of the risk organization, encompassing areas such as operational risk, financial crimes risk, technology and cyber risk, enterprise risk, business controls, and compliance.
Develop and optimize advanced Python scripts and SQL queries for data extraction and manipulation. Collaborate with stakeholders to understand analytic needs and reporting requirements and translate them into technical specifications. Ensure data integrity and accuracy in risk reporting processes. Assist in the continuous improvement of reporting workflows and methodologies. - Portfolio monitoring and risk limit setting Uses analytical techniques to provide insights into portfolio credit quality at segment level and assessment of emerging risk. Communicates findings and recommended enhancements to business partners and review remediation.
- Credit components (Data, Tools and Counter party) Develops monitoring for credit decision processes based on aggregation of component (models used in credit decisions, alt-data and other tools) risk and complexity. Designs and supports business cycle and credit impact assessments.
- Credit Review and Challenge Manages documentation, process, and standards for compliance with credit risk policy requirements. Assists in the compilation of the quarterly Chief Credit Risk Officer submissions. Documents and communicate results to senior leadership.
The above information is intended to describe the general nature and level of work performed by employees assigned to this job; it is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees in this role.
What You Have- Minimum Education, Skills and Experience Required Degree in statistics, economics, mathematics, or other quantitative science or equivalent, relevant work experience.
- Advance SQL coding required, with a minimum of 2yrs work experience using these languages.
- Experience with credit analytics, financial services, credit strategy or equivalent work experience.
- Applied experience using statistical tools (e.g., SAS, Python, R, Tableau etc.).
- 2 years of work experience building dashboards using PowerBI and the DAX coding language.
- Familiarity with credit policy, procedures, and standards.
- Be innovative - identify opportunities and drive actions.
- Strong understanding of regulatory environment.
- Has an inquisitive mindset.
- Strong oral and written communication skills as well as presentation skills.
- Strong organizational skills with attention to details.
- Strong team player who listens to stakeholders and works effectively toward solutions.
- Masters or PHD degree.
- Advance Python knowledge.
- Exposure to machine learning.
- Building dashboards using Tableau.
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