SAS Developer – Credit Risk

MUST BE ON W2 - NO THIRDPARTY RECRUITING/SUBVENDING Job Title: Senior Credit Risk Analyst – Predictive Modelling Location: Remote Start Date: ASAP Duration: 12 months (extension possible) Work Schedule: Monday–Friday, 37.5 hours/week Vacancies: 1 Role Overview We’re seeking a highly analytical and SAS-proficient Credit Risk Analyst to support data validation, predictive modelling, and dashboard development related to retail credit risk and expected credit loss (ECL) trends. This role will work closely with stakeholders across model validation, model risk management, technology, and retail credit product teams to enable effective risk oversight and decision-making. This is a remote role for a candidate with deep hands-on SAS skills, a strong grasp of statistical modelling, and familiarity with credit risk dynamics in financial services. Key Responsibilities • Validate, compile, and analyze large datasets across multiple retail product lines • Build SAS-based analytical pipelines to evaluate expected credit losses (ECL) and credit risk drivers • Design dashboards (e.g., Tableau) to visualize risk trends and portfolio performance • Support validation and documentation of predictive models, including scorecards and third-party models • Leverage machine learning techniques to identify data patterns and improve model performance • Collaborate with retail risk, finance, and product teams to translate analytics into actionable insights • Ensure adherence to model governance standards and regulatory expectations Must-Have Qualifications • 5+ years of experience in data analytics or predictive modelling, preferably in financial services • Strong hands-on proficiency in SAS (data manipulation, modelling, automation) • Familiarity with credit risk concepts, particularly in retail lending and ECL estimation • Experience with Python or Scala for supplementary model development or automation • Proven experience with machine learning algorithms for classification, regression, or clustering • Degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative discipline Nice-to-Have Skills • Experience with Tableau or other dashboarding tools • Familiarity with model validation, regulatory compliance, or internal audit frameworks • Exposure to Spark, R, or cloud-based analytics platforms • Advanced degree (MSc/PhD) in a relevant field