Location
London
Duration
20/12/2026
Days on site
2 days onsite
Pay-Rate
£402 per day all inc. (PAYE through Umbrella)
Responsibilities
- Design, develop, and implement statistical, pricing, or predictive models using SAS.
- Build modelling datasets, feature engineering pipelines, and variable transformations.
- Implement model logic, segmentation rules, scoring code, and scenario simulations.
- Translate business/model requirements into robust SAS code.
- Build efficient and reusable SAS programs using Base SAS, SAS Macros, Data Step, and SQL.
- Develop automated pipelines for model execution, scoring, and monitoring.
- Optimise SAS code for performance and scalability.
- Conduct back‑testing, model performance assessment, sensitivity checks, and stress testing.
- Validate datasets, assumptions, sampling methods, variable selection, and model accuracy.
- Prepare documentation for model testing, governance, and regulatory review.
- Analyse large structured datasets to derive patterns, insights, and business recommendations.
- Support teams with analytical outputs, trend analysis, and performance deep dives.
- Produce high‑quality artefacts such as model documentation, technical specifications, and impact analyses.
- Support scoring implementation, versioning, and production monitoring.
- Work with IT/Data Engineering teams to deploy models in controlled environments.
Qualifications
- 5–10+ years of SAS programming experience.
- Hands‑on experience with SAS SQL.
- Hands‑on experience with SAS Enterprise Guide or SAS Studio.
- Strong understanding of modelling concepts such as time‑series forecasting.
- Experience with model development lifecycle (MDLC) – development, testing, validation, documentation, and deployment.
- Strong data extraction, cleansing, transformation, and feature engineering skills.
- Experience working with large datasets and complex data workflows.
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