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Analyst – Model Risk & Data Analytics
RiskSpanUnited Statesfull_timeVerifiedPosted 19 May 2025
About the role
About RiskSpanRiskSpan is a leading source of analytics, modeling, data, and risk management solutions for the Consumer and Institutional Finance industries. We help financial institutions and regulators solve complex problems involving market, credit, and operational risk. Our clients include top banks, asset managers, servicers, and government-sponsored enterprises.Position OverviewWe are seeking a mid-level Analyst to support data-driven initiatives involving the model management lifecycle, including the development and validation of financial models and tools. The ideal candidate will have strong technical and communication skills, demonstrated Python proficiency, and experience gathering and documenting business requirements for regulated environments. Familiarity with second line of defense and model risk governance frameworks is a plus.Key Responsibilities
- Gather, document, and validate business and technical requirements for models and applications.
- Assist in documenting model methodologies and application processes to support 2nd Line of Defense reviews and other regulatory inquiries.
- Collaborate with cross-functional teams to define project scope and data needs.
- Perform data manipulation, analysis, and visualization using Python (Pandas, NumPy, etc.).
- Contribute to model lifecycle activities including model development, change management, implementation documentation, and validation support.
- Interpret model results and provide concise, actionable summaries for both technical and non-technical stakeholders.
- Maintain clear documentation of analytical processes, model assumptions, limitations, and business logic.
- Bachelor’s degree in Finance, Statistics, Economics, Applied Mathematics, Computer Science, or a related discipline.
- 2–5 years of experience in data analysis, quantitative modeling, or model governance in the financial services sector.
- Strong Python programming skills, including data handling and analysis with libraries such as Pandas, NumPy, and SciPy.
- Experience with SQL and working with structured data sets.
- Ability to communicate effectively with both technical and business stakeholders.
- Familiarity with model governance frameworks and second line of defense practices is preferred.
- Experience documenting models and applications for regulatory or audit review is a plus.
- Detail-oriented with strong analytical and problem-solving skills.
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