At a Glance
- Tasks: Develop and deploy AI solutions for compliance, risk, and contractor analytics.
- Company: Growing engineering business in Cardiff with a collaborative culture.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Join a dynamic team with a focus on innovation and best practices.
- Why this job: Make a real impact on AI projects that shape the future of technology.
- Qualifications: Experience in Data Science, ML models, and cloud platforms like AWS or Azure.
The predicted salary is between 40000 - 50000 £ per year.
We're supporting a growing engineering business looking to hire a Data Scientist to help develop scalable ML and AI solutions across compliance, risk and contractor analytics platforms. You'll work closely with AI Engineers, Data Engineers and DevOps teams to build and deploy predictive models and LLM-powered solutions in production environments across AWS and Azure.
This is a hands‑on opportunity to work on modern AI and machine learning initiatives that directly support operational performance, compliance and risk management. You'll be involved in the full model lifecycle from data ingestion and feature engineering through to deployment, optimisation and monitoring.
Key Responsibilities- Develop machine learning models for risk scoring, churn prediction and contractor analytics
- Build LLM and NLP solutions for automated compliance checks and insight generation
- Deploy AI and ML models into cloud‑based production environments
- Work with Microsoft Fabric for data ingestion, transformation and feature engineering
- Improve model monitoring, retraining and optimisation processes
- Collaborate closely with engineering and product teams in agile delivery squads
- Communicate technical solutions clearly to non-technical stakeholders
- Contribute to best practices around coding standards, maintainability and AI‑assisted development
- Python
- SQL
- TensorFlow
- PyTorch
- AWS
- Azure
- Microsoft Fabric
- NLP
- LLMs
- MLOps
- Strong commercial Data Science experience
- Experience building and deploying ML models into production
- Strong understanding of predictive modelling, NLP and LLM architectures
- Cloud experience with AWS and/or Azure
- Experience with Python, SQL and modern ML frameworks
- Strong communication and stakeholder management skills
- Ability to work collaboratively in agile engineering teams
- Risk modelling or compliance analytics
- Supply chain or operational analytics
- MLOps and CI/CD pipelines
- Data governance or regulatory environments
You'll join a collaborative engineering environment working on genuinely impactful AI projects with modern tooling and cloud technologies. This is an opportunity to help shape the future direction of AI capability within a growing business while working on real‑world applications of LLMs and predictive analytics.
Data Scientist. Job in Cardiff LilyLifestyle Jobs employer: United Cerebral Palsy of Georgia
Join a forward-thinking engineering business in Cardiff, where you'll thrive in a collaborative and innovative work culture that values your contributions to impactful AI projects. With a focus on employee growth, we offer opportunities for professional development and hands-on experience with cutting-edge technologies in a hybrid working environment. Enjoy the unique advantage of being part of a team that is shaping the future of AI while working on real-world applications that enhance operational performance and compliance.
Contact Details:
United Cerebral Palsy of Georgia Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist. Job in Cardiff LilyLifestyle Jobs
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML models or AI solutions. Share it on platforms like GitHub or your personal website, and don’t forget to link it in your applications.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t just apply anywhere; focus on companies that excite you! Use our website to find roles that match your skills and interests. Tailor your approach to each company, showing them why you’re the perfect fit for their team.
We think you need these skills to ace Data Scientist. Job in Cardiff LilyLifestyle Jobs
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning models, predictive analytics, and cloud technologies like AWS and Azure. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and data science, and how your background makes you a perfect fit for our team. Keep it engaging and relevant to the job description.
Showcase Your Technical Skills:When applying, make sure to mention your proficiency in Python, SQL, and any ML frameworks you’ve worked with. We love seeing examples of your work, so if you have any projects or GitHub repositories, include those too!
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 shows you’re keen on joining our team!
How to prepare for a job interview at United Cerebral Palsy of Georgia
✨Know Your Tech Stack
Make sure you’re familiar with the tools mentioned in the job description, like Python, SQL, TensorFlow, and AWS. Brush up on your knowledge of predictive modelling and NLP, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built and deployed ML models. Be ready to explain your role in the full model lifecycle, from data ingestion to deployment, and how you tackled challenges along the way.
✨Communicate Clearly
Since you'll need to explain technical solutions to non-technical stakeholders, practice simplifying complex concepts. Use examples from your past experiences to illustrate your points clearly and effectively.
✨Collaborate and Engage
Highlight your experience working in agile teams. Be prepared to discuss how you’ve collaborated with engineers and product teams, and share examples of how you contributed to best practices in coding standards and AI development.
