Are you passionate about leveraging advanced statistical methods to drive ground-breaking results in Breath Biopsy research?
We are seeking a highly skilled and motivated individual to join our innovative team. As a key member of our biostatistics team, you will be crucial in analysing and interpreting complex data as part of our research, clinical trials and support customer studies. You will also develop statistical models impacting our Breath Biopsy research direction. As part of your role, you will work alongside cross-functional teams and collaborate with major pharmaceutical companies and world-renowned research institutions.
Responsibilities
- Be an innovative and creative part of a team of scientists and engineers developing novel approaches to help achieve the company's mission
- Contribute with your expertise towards a wide spectrum of statistical aspects and initiatives, including the design of clinical studies, biomarker discovery and business development
- Evaluate existing tools and methods, propose suggestions for improvements and further develop the underlying algorithms and methods
- Support the design, expansion, and maintenance of effective data processing and statistical analysis pipelines and data visualisation tools for experimental and clinical studies
- Develop new and refine existing statistical analysis processes in close collaboration with other scientists and clinicians, to maximise the sensitivity and specificity of studies and trials
- Prepare study design and analysis protocols, reports, presentations, etc to communicate key insights and findings to stakeholders and customers
- Pro-actively seek learning and development opportunities and always aim to share knowledge with others
Requirements
Essential
- Degree in biostatistics, statistics, mathematics or a related quantitative or scientific subject
- Experience with Python, R, or alternatives
- Fundamental understanding of probability and statistics (e.g. power/sample size analysis, hypothesis testing, parametric and non-parametric methods, multivariate statistical tests, covariate analyses)
- Excellent interpersonal, oral and written communication skills
- Curiosity, eagerness to learn and a highly collaborative style
Desirable
- Basic knowledge of biology and/or chemistry
- Experience in applying statistical methods to real-world data sets (e.g. clinical trials); preferably in the pharmaceutical industry or working with contracted research organisations
- Experience in healthcare, biology or biotechnology. Experience working with mass spectroscopy-based metabolomics (or other omics data) derived from clinical trial or epidemiology/cohort studies is a plus
- Knowledge of targeted and non-targeted biomarker discovery
- Experience with more advanced statistical models such as mixed-effects models is a plus
- Understanding of different machine learning algorithms and their domain applicability in a production environment is a plus
- Familiarity with network analysis methods
- Basic knowledge of software engineering (e.g. SOLID, software development life cycle, design patterns, architectures) best practices
- Familiarity with Git, CI/CD best practices
- Familiarity with database management systems (relational and document-based)
- Familiarity with Agile methodologies and experience managing projects using Agile to ensure flexible and efficient project delivery
- Experience in recognising, quantifying and addressing sources of bias and variance
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