At a Glance
- Tasks: Design and develop predictive models using SAS, transforming data into actionable insights.
- Company: Global recruitment specialist with a focus on innovative solutions across multiple regions.
- Benefits: Competitive pay rate of £402 per day, flexible work environment, and career growth opportunities.
- Other info: Shortlisting within 48 hours for quick feedback and potential career advancement.
- Why this job: Join a dynamic team and make an impact through advanced data analysis and model development.
- Qualifications: 5-10+ years of SAS programming experience and strong analytical skills required.
The predicted salary is between 30000 - 40000 £ per year.
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Location: London
Duration: 20/12/2026
Days on site: 2 days onsite
Pay-Rate: £402 per day all inc. (PAYE through Umbrella)
Role Description:
- SAS Model Development & Enhancement (SAS Model Developer)
- 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.
- SAS Programming (Mandatory)
- Build efficient and reusable SAS programs using Base SAS, SAS Macros, Data Step, SQL.
- Develop automated pipelines for model execution, scoring, and monitoring.
- Optimise SAS code for performance and scalability.
- Model Validation & Testing
- 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.
- Data Analysis & Insight Generation
- 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.
- Model Deployment & Productionisation
- Convert prototype/model logic into production-ready SAS code.
- Support scoring implementation, versioning, and production monitoring.
- Work with IT/Data Engineering teams to deploy models in controlled environments.
Required Skills & Experience:
- 5–10+ years of SAS programming experience.
- Hands-on experience in:
- SAS Base, SAS Macros, Data Step programming
- SAS SQL
- SAS Enterprise Guide or SAS Studio
- Strong understanding of modelling concepts such as:
- Regression (linear/logistic)
- Time-series forecasting
- Segmentation models
- Risk, pricing, or predictive modelling
- 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.
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often shortlisted within 48 hours.
Programista Linux employer: eTeam
As a leading global recruitment specialist, we pride ourselves on fostering a dynamic and inclusive work culture that prioritises employee growth and development. Located in the vibrant city of London, we offer competitive pay rates and flexible working arrangements, ensuring our team members can thrive both professionally and personally. Join us to be part of a collaborative environment where your contributions are valued and impactful.
StudySmarter Expert Advice🤫
We think this is how you could land Programista Linux
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your SAS skills. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 3
Follow up after interviews! A quick thank-you email can go a long way in keeping you top of mind. It shows your enthusiasm and professionalism, which employers love.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Programista Linux
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the SAS Engineer role. Highlight your relevant experience with SAS programming and model development. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects where you've designed or implemented statistical models. We love seeing real examples of your work, so don’t hold back on the details!
Keep It Clear and Concise:Your application should be easy to read. Use bullet points and clear headings to make it skimmable. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at eTeam
✨Know Your SAS Inside Out
Make sure you brush up on your SAS programming skills, especially Base SAS, SAS Macros, and SQL. Be ready to discuss specific projects where you've implemented these skills, as well as any challenges you faced and how you overcame them.
✨Understand the Modelling Concepts
Familiarise yourself with key modelling concepts like regression, time-series forecasting, and segmentation models. Prepare to explain how you've applied these concepts in past roles, and be ready to discuss the model development lifecycle in detail.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of model validation, testing, and deployment. Think about examples from your experience where you conducted back-testing or performance assessments, and be prepared to walk through your thought process.
✨Showcase Your Data Analysis Skills
Be ready to discuss how you've analysed large datasets to derive insights and business recommendations. Bring examples of high-quality artefacts you've produced, such as model documentation or impact analyses, to demonstrate your analytical capabilities.
