SAS Engineer - Insurance Domain

This role focuses on SAS-based model development, enhancement, validation, and deployment across pricing, risk, and predictive modelling domains. You will work on building end-to-end statistical models, developing robust SAS code, preparing high-quality documentation, conducting model testing, and supporting productionisation activities. The role requires strong analytical abilities, SAS programming expertise, and hands-on experience throughout the Model Development Lifecycle (MDLC). Hybrid working:

The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time. Your Role:

• Develop and enhance predictive, pricing, and statistical models using SAS.
• Build modelling datasets and perform feature engineering.
• Implement model logic, scoring code, and segmentation rules.
• Write efficient SAS programs for modelling and analysis.
• Perform model testing, backtesting, and validation checks.
• Analyse large datasets to generate insights and recommendations.
• Convert prototype models into production-ready SAS code.
• Collaborate with IT/Data Engineering for model deployment and monitoring.

• 5-10 years of strong SAS programming experience.
• Expertise in Base SAS, SAS Macros, Data Step, and SAS SQL.
• Experience with SAS EG or SAS Studio.
• Strong understanding of regression, forecasting, and segmentation models.
• Hands-on experience in the full model development lifecycle (MDLC).
• Strong data extraction, cleansing, and feature engineering capability.
• Ability to work with large datasets and complex workflows.
• Strong analytical, documentation, and problem-solving skills.

Capgemini ist einer der weltweit führenden Anbieter von Management- und IT-Beratung, Technologie-Services und Digitaler Transformation. Als ein Wegbereiter für Innovation unterstützt das Unternehmen seine Kunden bei deren komplexen Herausforderungen rund um Cloud, Digital und Plattformen.