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 ta.admin@acuityanalytics.

For more details about Acuity Analytics please see here

• Read here
• .