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Tier-1 consulting brand, popular data-science role, mid-level experience band, metro location, and broad skill requirements.
Role is heavily credit-risk and finance-focused, limiting direct transferability across unrelated industries.
Explicit 3–8 years plus mandatory credit-risk modeling, model governance knowledge, and specific tooling increases filter strictness.
Develop, implement, and validate credit risk and financial models including PD, LGD, EAD, IFRS 9/ECL, stress testing, and provisioning.
Translate business and risk requirements into quantitative solutions covering data preparation, methodology design, implementation, and performance assessment.
Collaborate with partners and client stakeholders to deliver high-quality models, documentation, and communication across risk, finance, and technology teams.
3 to 8 years experience in credit risk quantitative modelling, model development, or validation (IRB, CECL, IFRS9, predictive modeling, forecasting).
Bachelor’s or master’s degree in a quantitative discipline such as Statistics, Mathematics, Economics, Finance, Engineering, Computer Science, or Data Science.
Proficiency in Python and SQL; experience with SAS, R, Spark, or cloud analytics is a plus.
Experience with Model Risk Management frameworks, including knowledge of governance standards like SR 11-7, E-23, CP6-22/SS1-23, and model risk monitoring.
Comfortable working independently in a fast-paced consulting environment with strong ownership and attention to detail on model development and delivery.
Experienced in financial services or consulting contexts involving credit risk, portfolio analytics, and regulatory model compliance.
Effective at clear technical communication for mixed technical and business audiences and collaborating with global teams across time zones.