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: Engage in a collaborative 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 strong data analysis skills.
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 in London 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 projects in a large-scale data and analytics setting. With competitive rates and a supportive atmosphere, we are committed to empowering our employees to thrive and succeed in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land SAS Model Developer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data and analytics field. Attend meetups or webinars related to SAS and model development. You never know who might have a lead on that perfect role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SAS projects, especially those involving predictive models. 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 past projects and how you tackled challenges during the model development lifecycle. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented SAS Model Developers like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace SAS Model Developer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your SAS programming experience and any relevant projects you've worked on. We want to see how your skills match the job description, so don’t be shy about showcasing your expertise in model development and data analysis!
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 SAS and how you’ve tackled challenges in model development. We love a good story!
Showcase Your Technical Skills:When filling out your application, make sure to mention your experience with Base SAS, SAS Macros, and SAS SQL. We’re looking for someone who can hit the ground running, so let us know how you’ve used these tools in your previous roles.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it’s super easy – just follow the prompts and you’ll be all set!
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 prepared to discuss specific projects where you've used these tools, and maybe even demonstrate your coding prowess if asked.
✨Showcase Your Model Development Experience
Be ready to talk about the full model development lifecycle you've been involved in. Highlight your experience with statistical, predictive, and pricing models, and share examples of how you've tackled challenges during model testing and validation.
✨Data Analysis is Key
Since this role involves analysing large datasets, come prepared with examples of how you've identified trends and insights from data. Discuss your approach to feature engineering and how it has impacted your modelling outcomes.
✨Collaboration is Crucial
This position requires working closely with data engineering and technology teams. Be ready to share experiences where you've collaborated effectively with others, and how you ensured smooth implementation and deployment of models in controlled environments.
