At a Glance
- Tasks: Apply advanced analytics and data science to improve public health across Wales.
- Company: Public Health Wales, dedicated to enhancing health outcomes.
- Benefits: Flexible working, professional development, and meaningful impact on health.
- Other info: Collaborative culture with opportunities for growth and innovation.
- Why this job: Shape the future of data science while making a real difference in communities.
- Qualifications: Master's degree in data science or related field; experience in end-to-end projects.
The predicted salary is between 45000 - 55000 £ per year.
In this role you will apply advanced analytics, modelling and data science to support national public health priorities across Wales. You will collaborate with multidisciplinary teams, deliver end-to-end data science projects, and shape the future of data science within Public Health Wales. You’ll work with cloud-based tech and communicate complex insights to diverse audiences, contributing to improvements in health outcomes and reduced inequalities.
Pay / Benefits
- Flexible working opportunities for professional development
- Meaningful impact on public health outcomes
- Collaborative culture supportive of flexible working arrangements
Responsibilities
- Perform statistical and simulation modelling, machine learning, predictive analytics and data engineering on diverse datasets
- Work with modern cloud-based technologies and document data pipelines
- Collaborate with multidisciplinary teams and stakeholders to define requirements and deliver impact
- Contribute to shaping the organisation's data science practices and governance
- Communicate complex findings clearly to technical and non-technical audiences
Key requirements
- Master's degree in data science, computer science, or software engineering (or equivalent)
- Experience delivering data science projects end-to-end with stakeholder engagement
- Agile experience working in multidisciplinary teams and ability to coach others in data science
- Enthusiastic and proactive mindset
- Strong communication and presentation skills
- Team player with negotiation and diplomacy abilities
- Advanced R and/or Python with reproducible analytical pipelines
- Git and GitHub for version control and collaboration
- Statistical and data science methods (projections, modelling, ML, econometrics, regression, causal inference) including model validation and uncertainty
Advanced Data Scientist in Cardiff employer: National Health Service
Betsi Cadwaladr University Health Board is an exceptional employer, offering a supportive and collaborative work environment for healthcare professionals in North Wales. With a commitment to employee development and a focus on compassionate care, staff have access to continuous professional development opportunities and the chance to make a meaningful impact in both acute and community paediatrics. The Health Board's integrated approach ensures that employees are part of a dynamic team dedicated to improving health outcomes for the local population.
StudySmarter Expert Advice🤫
We think this is how you could land Advanced Data Scientist in Cardiff
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like National Health Service.
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We think you need these skills to ace Advanced Data Scientist in Cardiff
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at National Health Service, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at National Health Service. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at National Health Service
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at National Health Service!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
