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SAS Engineer - Insurance Domain

Remote / Online - Candidates ideally in
London, Greater London, W1B, England, UK
Listing for: Capgemini
Remote/Work from Home position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer
Job Description & How to Apply Below
SAS Engineer - Insurance Domain - London Reference Code:

- Type:

Permanent Professional Communities:
Data & AI

About the Job you are considering:

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:

INSURANCE DOMAIN EXPERIENCE IS MUST

  • 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.

Your

Skills:

  • 510 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.

We are a Disability Confident

Employer:

Capgemini is proud to be a

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