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For Companies At a Glance
- Tasks: Analyse data, build datasets, and develop AI workflows for innovative construction tech.
- Company: Join Asite, a leader in smart construction technology with global impact.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional growth.
- Why this job: Shape the future of construction with cutting-edge AI and data science.
- Qualifications: Strong stats background, Python proficiency, and experience with data pipelines.
- Other info: On-site role in London with a dynamic team focused on AI innovation.
The predicted salary is between 50000 - 70000 £ per year.
We start with a simple idea: the built environment should be smarter, safer and more sustainable. Everything we do is about helping the people behind major construction and infrastructure projects work together more easily and make better decisions. Asite offers a cloud-based platform that connects project teams, improves collaboration and manages data from the first design to the final handover. Industry leaders such as Laing O’Rourke, Transport for London, MTA New York and Aldar use Asite to keep their projects running smoothly and delivering strong results.
With offices around the world and a record of steady, profitable growth, we are shaping the future of construction technology while supporting the people who build the world around us.
The Role
As an AI Data Scientist at Asite, you will work closely with our AI and Product teams to design, build, and deploy data workflows that support machine learning, analytics, and model development. You’ll help us evaluate and label large volumes of structured and unstructured data, prepare clean datasets, and support the development of new AI capabilities powered by LLMs, embeddings, and vector search. This is an on-site role in our London office, working alongside a growing team focused on scaling our internal AI capabilities.
What You’ll Be Doing
- Analyse and classify structured and unstructured data from across the platform
- Build clean, reliable datasets and automated ETL workflows
- Develop prototypes in Python using pandas, numpy, scikit-learn, and related libraries
- Support experiments with LLMs, embeddings, and vector search technologies
- Work with cloud services (GCP / AWS / Azure) for model deployment and pipeline automation
- Collaborate with engineers and product teams to integrate data workflows into AI features
- Document processes, tools, and analysis outputs clearly and consistently
- Apply production-quality coding practices including Git, API usage, and modular design
What You Bring
- Strong foundation in statistics, data analysis, and machine learning fundamentals
- Proficiency in Python and common data science tooling
- Experience preparing datasets and building automated pipelines
- Comfortable working with both structured and unstructured data
- Familiarity with cloud platforms (GCP / AWS / Azure)
- Understanding of APIs, Git, and robust coding standards
Nice to Have
- Experience working with LLMs, embeddings, or vector databases
- Exposure to NLP, classification, or document understanding problems
- Experience with data visualisation (Tableau, Power BI, or Python libraries)
- Background in deploying ML models in production environments
AI Data Scientist in London employer: Asite
Contact Detail:
Asite Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. The more you engage, the better your chances of landing that AI Data Scientist role at Asite.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, machine learning, and data workflows. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with cloud platforms and data pipelines, as these are key for the role at Asite.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the Asite team.
We think you need these skills to ace AI Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Data Scientist role. Highlight your proficiency in Python, data analysis, and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our goals at Asite. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any cool data science projects, don’t hold back! Include links to your GitHub or any relevant portfolios. We’re keen to see your hands-on experience with machine learning and data workflows.
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’re considered for the role. Plus, it gives you a chance to explore more about what we do at Asite!
How to prepare for a job interview at Asite
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in both structured and unstructured data analysis. Brush up on your experience with Python libraries like pandas and scikit-learn, as you'll likely be asked to discuss how you've used them in past projects.
✨Showcase Your Cloud Knowledge
Familiarity with cloud platforms is key for this role. Be prepared to talk about your experience with GCP, AWS, or Azure, especially in relation to model deployment and pipeline automation. Having specific examples ready will help demonstrate your expertise.
✨Prepare for Technical Questions
Expect technical questions that dive into machine learning fundamentals and coding practices. Brush up on your understanding of APIs, Git, and modular design. Practising coding problems beforehand can give you a confidence boost.
✨Collaborate and Communicate
As collaboration is crucial in this role, think of examples where you’ve worked closely with engineers or product teams. Highlight your ability to document processes clearly and communicate effectively, as these skills are essential for integrating data workflows into AI features.