At a Glance
- Tasks: Design and develop predictive models using SAS in a dynamic data environment.
- Company: Join a leading analytics firm in London with a hybrid work model.
- Benefits: Competitive daily rate, flexible working, and opportunities for skill enhancement.
- Other info: Collaborative team environment with potential for contract extension.
- Why this job: Make an impact by optimising models that drive business insights and decisions.
- Qualifications: Hands-on SAS programming experience and knowledge of model development lifecycle.
The predicted salary is between 96000 - 96000 £ per year.
Location: London (Hybrid - 2 days onsite per week)
Rate: £400/day Inside IR35
Duration: 3-month rolling contract
Overview: We're looking for an experienced SAS Model Developer to support model development, enhancement, and deployment across a large-scale data and analytics environment. This role will focus on building and optimising SAS-based models, supporting the full model development lifecycle from data preparation and feature engineering through to testing, validation, and production deployment.
Key Responsibilities
- Design, develop, and enhance statistical, predictive, and pricing models using SAS
- Build modelling datasets, feature engineering pipelines, and variable transformations
- Develop SAS programs using:
- Base SAS
- SAS Macros
- Data Step
- SAS SQL
- Support automated model execution, scoring, and monitoring processes
- Conduct model testing, validation, back-testing, and performance analysis
- Analyse large datasets to identify trends, patterns, and business insights
- Produce technical documentation, model artefacts, and governance outputs
- Support deployment and productionisation of models within controlled environments
- Work closely with data engineering and technology teams to support implementation
What We're Looking For
- Strong hands-on SAS programming experience
- Experience across:
- SAS Base
- SAS Macros
- SAS SQL
- SAS Enterprise Guide / SAS Studio
- Experience developing and deploying predictive or statistical models
- Strong understanding of: Regression models, Forecasting, Segmentation, Risk or pricing models
- Experience working across the full model development lifecycle
- Strong data analysis, transformation, and feature engineering capability
- Comfortable working with large and complex datasets
SAS Model Developer employer: TXP
Join a dynamic and innovative team in London as a SAS Model Developer, where you'll have the opportunity to work in a hybrid environment that promotes flexibility and work-life balance. Our company fosters a collaborative culture that values continuous learning and professional growth, offering you the chance to enhance your skills while contributing to impactful data-driven projects. With competitive rates and a supportive atmosphere, we are committed to providing a rewarding experience for our employees.
StudySmarter Expert Advice🤫
We think this is how you could land SAS Model Developer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data and analytics field. Let them know you're on the lookout for SAS Model Developer roles. You never know who might have the inside scoop on an opportunity!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SAS projects, especially those involving model development and deployment. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common SAS-related questions and scenarios. Practice explaining your experience with model testing, validation, and feature engineering. Confidence is key, so let your expertise shine!
✨Tip Number 4
Don't forget to apply through our website! We’ve got some fantastic opportunities waiting for talented SAS Model Developers like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace SAS Model Developer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your SAS programming experience and any relevant model development projects. We want to see how your skills match the job description, so don’t be shy about showcasing your expertise in Base SAS, SAS Macros, and SQL.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the SAS Model Developer role. Share specific examples of your work with predictive models and how you've tackled challenges in the past.
Showcase Your Projects:If you’ve worked on any interesting projects involving model development or data analysis, make sure to mention them. We love seeing real-world applications of your skills, especially if they relate to regression, forecasting, or pricing models.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates regarding your application status!
How to prepare for a job interview at TXP
✨Know Your SAS Inside Out
Make sure you brush up on your SAS programming skills, especially Base SAS, SAS Macros, and SAS SQL. Be ready to discuss specific projects where you've developed or enhanced models using these tools, as this will show your hands-on experience.
✨Showcase Your Model Development Process
Prepare to walk through the full model development lifecycle in your previous roles. Highlight your experience with data preparation, feature engineering, testing, and validation. This will demonstrate your comprehensive understanding of the process and your ability to contribute effectively.
✨Bring Data Analysis Examples
Have a few examples ready where you've analysed large datasets to extract trends and insights. Discuss the techniques you used for data transformation and feature engineering, as this will showcase your analytical skills and problem-solving abilities.
✨Communicate Clearly and Confidently
During the interview, focus on clear communication, especially when discussing technical concepts. Practice explaining complex ideas simply, as you'll need to collaborate with data engineering and technology teams. Confidence in your delivery can make a big difference!
