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- Tasks: Design and deploy Bayesian models, develop data pipelines, and create insightful dashboards.
- Company: Join a dynamic team focused on data science and analytics innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and development.
- Why this job: Make a real impact by solving complex business problems with data-driven insights.
- Qualifications: Experience in Bayesian modelling, Python, R, and AWS is essential.
The predicted salary is between 50000 - 70000 ÂŁ per year.
We are seeking a highly capable Data Scientist with strong experience in Bayesian hierarchical modelling and advanced statistical techniques to join a growing data and analytics capability. This role sits across data science, data engineering, and backend development, supporting the delivery of scalable models, robust data pipelines, and high-quality insight products. You will work with complex, high-volume datasets, applying statistical rigour to solve real business problems, while also contributing to the engineering layer that enables analytics at scale.
Key Responsibilities
- Design, build, and deploy Bayesian hierarchical models to support forecasting, inference, and decision-making.
- Develop and maintain data pipelines and ETL processes, ensuring reliable, clean, and well-structured datasets.
- Contribute to data “plumbing” and backend data services that support analytics and modelling workflows.
- Work with large and complex datasets using Python and R.
- Build and deploy scalable data solutions within AWS environments (e.g. S3, Glue, Lambda, Redshift, or equivalent services).
- Develop dashboards and data visualisations to translate complex model outputs into clear, actionable insights for stakeholders.
- Support backend development where required, particularly around data APIs, pipelines, and integration layers.
- Collaborate with data engineers, analysts, and business stakeholders to define requirements and deliver end-to-end solutions.
- Ensure model performance, validation, monitoring, and continuous improvement.
- Contribute to best practices across data science, engineering, and cloud-based data architecture.
Key Skills
Data Science Specialist employer: LHH
Contact Detail:
LHH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Specialist
✨Tip Number 1
Network like a pro! Reach out to folks in the data science community, attend meetups, and connect 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 Bayesian hierarchical models and any cool projects you've worked on. This is your chance to demonstrate your expertise in R, Python, and AWS – make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the business problems you’ll be solving. Practice explaining your thought process clearly, especially around complex datasets and model performance.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for talented Data Science Specialists like you. It’s the best way to get noticed and land that dream job!
We think you need these skills to ace Data Science Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Bayesian hierarchical modelling and the tools we use, like R and Python. We want to see how your skills match up with what we're looking for!
Showcase Your Projects: Include specific examples of projects where you've built and deployed models or worked with large datasets. This helps us understand your hands-on experience and how you tackle real business problems.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and how it relates to the role. We appreciate a well-structured application that gets to the point!
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’s super easy!
How to prepare for a job interview at LHH
✨Know Your Bayesian Hierarchical Modelling
Make sure you brush up on your knowledge of Bayesian hierarchical modelling. Be ready to discuss how you've applied this technique in past projects, and think about specific examples where it made a significant impact on your results.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python and R. You might be asked to solve a problem on the spot, so practice coding challenges related to data manipulation and statistical analysis to show off your skills.
✨Familiarise Yourself with AWS Services
Since the role involves working with AWS, make sure you understand the key services mentioned in the job description, like S3 and Lambda. Be ready to discuss how you've used these tools in previous roles or projects.
✨Communicate Insights Clearly
You’ll need to translate complex data findings into actionable insights for stakeholders. Prepare to explain how you would present your model outputs and visualisations in a way that’s easy to understand, perhaps by using a past example.