Senior Data Scientist (Biostatistics)

Please note that for this role, you must be based in the UK or Portugal.

About us 
Ascent has recently been acquired by  Acuity Analytics .  This is both a significant milestone for us and a tremendous opportunity for you.  Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans.  We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations.  To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency. 

About the role

We are looking for a Senior Data Scientist (Biostatistics) to support our clients in advancing their statistical modelling capabilities.

In this role, you will work closely with client-side biostatisticians and cross-functional teams to refine modelling approaches, design robust and scalable R-based processes, and support the deployment of statistical models as production-grade software on cloud infrastructure.

This is a highly collaborative and consultative position where you’ll act as a technical expert and advisor—helping clients bridge statistical science with modern engineering best practices. You’ll ensure models are reproducible, maintainable, and production-ready, while enabling teams to adopt more efficient, scalable, and AI-accelerated ways of working.

Skills and Experience required 

Core skills:

• Strong background in statistics, ideally with experience as a biostatistician
• Advanced proficiency in R , including package development
• Solid experience with version control (Git) and collaborative workflows
• Experience with CI/CD pipelines , automated testing, and documentation practices
• Strong understanding of reproducible research and robust statistical modelling practices
• Experience using AI-assisted development tools to accelerate coding, testing, documentation, debugging, and technical problem solving

Technical and platform experience:

• Experience designing scalable R-based processes for modelling workflows
• Familiarity with deploying models or analytical workflows into production environments
• Experience with Databricks or similar cloud-based data platforms
• Exposure to API development or integration (nice to have)
• Awareness of common AI and LLM integration patterns, such as API-based integration, retrieval-augmented generation, workflow automation, tool/function calling, and human-in-the-loop review

Soft skills:

• Excellent written and verbal communication skills
• Ability to translate complex statistical concepts into clear, practical guidance
• Strong stakeholder engagement and advisory mindset
• Ability to apply sound judgement when using AI tools, ensuring outputs are reviewed, validated, and appropriate for regulated environments

What you will do

• Collaborate closely with biostatisticians and cross-functional teams
• Refine and enhance statistical modelling approaches and methodologies
• Design and develop robust R-based workflows and packages
• Implement best practices for testing, documentation, and CI/CD in statistical projects
• Support the deployment of models as scalable, production-ready software on cloud platforms
• Provide technical guidance and mentorship to improve modelling and engineering standards
• Ensure reproducibility, maintainability, and performance of statistical solutions
• Use AI-assisted development tools to improve delivery speed, code quality, testing, documentation, and refactoring
• Identify practical opportunities to apply LLMs or AI-enabled tooling within modelling, analytics, engineering, or knowledge workflows

Why join us 

People are at the Heart of our Business.  By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.  Check out  this page for more details.

If you have any questions contact our Talent Acquisition team on View email address on ascent.applytojob.com.

For more details about Acuity Analytics please see here: Read here .