At a Glance
- Tasks: Develop and deploy AI solutions for compliance, risk, and contractor analytics.
- Company: Growing engineering business with a focus on innovative AI projects.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on agile delivery and career development.
- Why this job: Make a real impact in AI while working with cutting-edge technologies.
- Qualifications: Experience in Data Science, ML models, and cloud platforms like AWS or Azure.
The predicted salary is between 50000 - 65000 € 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 in City employer: Yolk Recruitment
Join a forward-thinking engineering business in Cardiff, where you'll thrive in a collaborative and innovative work culture focused on impactful AI projects. With opportunities for professional growth and development, you will be part of a dynamic team that values your contributions and encourages continuous learning in the rapidly evolving fields of machine learning and predictive analytics. Enjoy the benefits of a hybrid working model, modern tooling, and the chance to shape the future of AI solutions in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in City
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning models and projects. Use platforms like GitHub to share your code and demonstrate your expertise in Python, SQL, and modern ML frameworks.
✨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 forget to apply through our website! We love seeing applications from passionate candidates who are eager to join our collaborative engineering environment and work on impactful AI projects.
We think you need these skills to ace Data Scientist in City
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your experience with machine learning, predictive modelling, and any cloud technologies like AWS or Azure. We want to see how you can contribute to our AI projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our needs. Don’t forget to mention specific projects or achievements that showcase your skills in ML and AI.
Showcase Your Technical Skills:In your application, be sure to highlight your proficiency in Python, SQL, and any ML frameworks you've worked with, like TensorFlow or PyTorch. We love seeing practical examples of your work, so feel free to include links to your GitHub or any relevant projects.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at Yolk Recruitment
✨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 techniques, as these will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built and deployed ML models. Highlight your role in the full model lifecycle, from data ingestion to deployment, and be ready to explain the impact of your work on operational performance or compliance.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with non-technical stakeholders, so think about how you can break down your past experiences into relatable stories.
✨Collaborate and Engage
Demonstrate your ability to work in agile teams by sharing examples of collaboration. Discuss how you’ve worked closely with engineers and product teams, and be prepared to talk about how you handle feedback and adapt to changes in project requirements.
