At a Glance
- Tasks: Transform complex healthcare data into impactful solutions using advanced analytics and AI.
- Company: Join The Craneware Group, a leader in healthcare technology innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on responsible innovation and career advancement.
- Why this job: Make a real difference in healthcare by leveraging cutting-edge data science techniques.
- Qualifications: Strong background in data science, programming skills in Python or R, and experience with machine learning.
The predicted salary is between 60000 - 80000 € per year.
At The Craneware Group, our Data Science team plays a critical role in shaping the future of healthcare technology. We work at the intersection of advanced analytics, machine learning, and AI—partnering closely with Engineering, Product, and the wider business to turn complex healthcare data into meaningful, real‐world outcomes.
As a Senior Data Scientist, you’ll join a collaborative, highly skilled team that values strong technical foundations, thoughtful problem‐solving, and responsible innovation. From improving existing products to helping catalyse new, data‐driven solutions, the team is constantly exploring how modern data science and generative AI can deliver measurable impact for healthcare providers.
- Significant hands‐on experience as a Data Scientist, with a strong track record of delivering measurable business or product impact
- A degree in a computational or quantitative discipline such as Data Science, Statistics, Engineering, Mathematics, Physics, or a related field
- Strong programming skills in Python or R, alongside solid experience using SQL and working with relational and large‐scale data sets
- Deep expertise in statistical modelling and machine learning, with practical experience taking models into production
- Experience designing and applying generative AI solutions, including working with large language models (LLMs) and prompt engineering
- Familiarity with data visualisation tools such as Tableau, Power BI, Qlik, or similar
- Experience working in cloud environments, ideally Microsoft Azure, with an understanding of modern data platforms
- A good understanding of MLOps practices, including versioning, monitoring, and automated deployment pipelines
- Experience working in Agile, CI/CD‐driven engineering environments and using ALM and source control tools (e.g. Jira, Azure DevOps, Git)
- Excellent communication skills, with the ability to explain complex ideas clearly and adapt messaging to different audiences
- A proactive, self‐motivated approach with the confidence to influence, collaborate, and continuously improve technical processes
- Experience working with healthcare, medical, or claims data is highly desirable
Senior Data Scientist in Edinburgh employer: Craneware
At The Craneware Group, we pride ourselves on being an exceptional employer, particularly for those in the Senior Data Scientist role. Our Edinburgh-based team thrives in a collaborative and innovative environment, where employees are encouraged to grow through continuous learning and development opportunities. With a strong focus on impactful healthcare technology, we offer a unique chance to work at the forefront of data science, contributing to meaningful outcomes while enjoying a supportive work culture that values creativity and teamwork.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to current employees at The Craneware Group on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data science projects, especially those involving machine learning and generative AI. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your technical skills, especially Python, SQL, and MLOps practices. You never know when a coding challenge might pop up during the interview process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior Data Scientist in Edinburgh
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your hands-on experience, programming skills in Python or R, and any relevant projects that showcase your expertise in statistical modelling and machine learning.
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 mission at The Craneware Group. Don’t forget to mention your experience with generative AI solutions!
Showcase Your Projects:If you've worked on any significant projects, especially those involving healthcare data or MLOps practices, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s straightforward, and we’re excited to see your application come through directly!
How to prepare for a job interview at Craneware
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially around statistical modelling and machine learning. Be ready to discuss how you've applied these in real-world scenarios, particularly in healthcare settings.
✨Showcase Your Technical Skills
Prepare to demonstrate your programming prowess in Python or R, and be ready to discuss your experience with SQL. You might even want to bring examples of projects where you’ve worked with large-scale datasets or implemented generative AI solutions.
✨Communicate Clearly
Practice explaining complex ideas in simple terms. The interviewers will want to see if you can adapt your messaging for different audiences, so think about how you would explain your work to someone without a technical background.
✨Familiarise Yourself with MLOps and Agile Practices
Understand the principles of MLOps and be prepared to discuss your experience with versioning, monitoring, and deployment pipelines. Also, brush up on Agile methodologies, as they are likely to be part of the team’s workflow.
