Data Scientist (Biostatistics)
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Job description
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., 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., * 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
Requirements
- 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
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