At a Glance
- Tasks: Enhance statistical modelling and develop scalable R-based workflows for life sciences.
- Company: Leading life sciences organisation focused on innovation and collaboration.
- Benefits: Up to £80,000 salary, hybrid work, and professional development opportunities.
- Other info: Join a dynamic team that values technical excellence and career growth.
- Why this job: Make a real impact in the life sciences sector with cutting-edge statistical solutions.
- Qualifications: Strong background in Biostatistics and advanced R programming skills required.
The predicted salary is between 55000 - 70000 £ per year.
We are seeking a Senior Data Scientist with a strong background in Biostatistics to help leading life sciences and pharmaceutical organisations modernise and scale their statistical modelling capabilities. This role combines statistical expertise with modern data engineering practices, enabling the development of robust, reproducible, and production-ready analytical solutions. You'll work closely with biostatisticians, data scientists, and technical stakeholders to improve modelling approaches and deploy scalable solutions within cloud-based environments.
Key Responsibilities
- Partner with biostatisticians and cross-functional teams to enhance statistical modelling methodologies
- Design and develop scalable R-based modelling workflows and packages
- Implement best practices for testing, documentation, version control, and CI/CD
- Support the deployment of statistical models into production environments
- Ensure analytical solutions are reproducible, maintainable, and performant
- Provide technical guidance and mentoring on statistical and engineering best practices
- Translate complex statistical concepts into practical business and technical solutions
Skills & Experience
Essential
- Strong statistical background, ideally within Biostatistics
- Advanced R programming skills, including package development
- Experience with Git and collaborative development workflows
- Knowledge of CI/CD pipelines, automated testing, and software engineering best practices
- Strong understanding of reproducible research and statistical modelling standards
- Excellent communication and stakeholder management skills
Desirable
- Experience designing and scaling R-based modelling platforms
- Exposure to deploying analytical models into production environments
- Experience with Databricks or similar cloud data platforms
- API development or integration experience
Why Apply?
This is an opportunity to work on high-impact projects within the life sciences sector, helping organisations bridge the gap between advanced statistical science and modern cloud-based engineering. You'll join a collaborative environment where technical excellence, innovation, and professional growth are highly valued.
Senior Data Scientist - Biostatistics in London employer: develop
Join a dynamic consultancy that prioritises employee growth and fosters a collaborative work culture in the heart of London. With a focus on health sector transformation, we offer competitive salaries, hybrid working options, and opportunities to lead impactful projects while mentoring the next generation of consultants. Our commitment to professional development ensures that you will thrive in an environment that values innovation and strategic thinking.
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We think you need these skills to ace Senior Data Scientist - Biostatistics in London
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
