Data Scientist
SR2
18 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
£ 52KJob location
Tech stack
Decision-Making Software
Python
Machine Learning
TensorFlow
Unstructured Data
PyTorch
Deep Learning
Scikit Learn
Information Technology
Job description
Are you a data-driven problem solver who thrives on turning complex information into actionable insight? We're seeking a Data Scientist to join a growing, research-focused organisation developing innovative predictive models to assess and manage risk.
This is a fantastic opportunity to work on cutting-edge projects where your analytical and machine learning expertise will directly influence high-impact decision-making tools.
What You'll Do
- Design, train, and validate machine learning models to predict and quantify risk using diverse, high-volume datasets.
- Work closely with data engineers and domain specialists to prepare, clean, and analyse structured and unstructured data.
- Apply advanced statistical, machine learning, and deep learning techniques to extract insights and improve predictive accuracy.
- Present findings and model outputs clearly to technical and non-technical audiences.
- Contribute to the ongoing development of ML workflows, tools, and best practices within the team.
Requirements
- MSc or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Proven experience building and deploying predictive models using Python and libraries such as scikit-learn, TensorFlow, PyTorch, etc
- Excellent problem-solving skills and attention to detail.
- Effective communicator with the ability to collaborate across disciplines.
- Comfortable working on site in Cardiff three days per week as part of a dynamic, collaborative team.
Benefits & conditions
Why Join Them?
- Play a key role in developing innovative data-driven solutions that address real-world challenges.
- Be part of an ambitious, supportive, and multidisciplinary environment where innovation is encouraged.
- Competitive salary and flexible working arrangements (hybrid model).
- Opportunities for professional growth and contribution to impactful research.