Principal Bioinformatics Data Scientist
Principal Bioinformatics Data Scientist
The AI and Analytics team within AstraZeneca’s R&D Data Science and AI group is where great things happen in applying sophisticated algorithms and techniques to some of the hardest problems in the discovery and development of new medicines. The team uses a blend of scientific, problem solving, and quantitative skills to develop and deliver ground breaking methods addressing critical problems in our R&D environment. Our team of data scientists work right next to our other scientists, allowing them to be close to the questions that matter and work on a broad range of the most promising opportunities quickly.
The Data Science & AI team collaborates across R&D to drive innovation through data science and AI. Together we seek to:
- Improve our understanding of disease and uncovering new targets
- Transform R&D processes
- Speed the design and delivery of new medicines for patients
Do you want to join us and apply machine learning to tackle difficult problems in drug development? As a Principal Data Scientist, you can play a pivotal role in a rapidly growing team analysing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients faster.
In this role, you will apply your expertise in bioinformatics, machine learning, quantitative data analysis and leadership to develop innovative data science solutions across multiple therapeutic areas (Respiratory, Inflammatory, Cardiovascular, Renal and Metabolism) in clinical drug development. To achieve this, you will scout new technologies/methods and work in a highly multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
We work on a flexible and varied portfolio of challenges that could include – but are not limited to:
- Develop, implement and support novel bioinformatics solutions designed to drive the interrogation of human disease biology. This includes data from signal pathway analysis, cellular characterization, integrated multi-omics technologies, and other systems biology methods for biomarker and target discovery.
- Researching and developing machine learning models, forecasting and optimization methods on multi-modal data to guide decision-making about and resourcing of our drug projects.
- Perform expert scientific research, including establishment of scientific hypothesis that can be approached using computational methods and tools. Present or publish findings for conferences and in peer reviewed journals.
- Build and manage effective relationships with stakeholders to insure utilization and value of information resources and services.
These challenges will require you to:
- Provide advanced data science expertise to cross-functional projects and drive delivery of data science solutions that drive value to AstraZeneca
- Apply a range of data science methodologies, developing novel data science solutions where off-the-shelf methodologies do not fit
- Translate unstructured, complex business problems into the appropriate data problem, model and analytical solutions
- Leads small (2-3 person) data science projects of defined scope
- Developing, maintaining and applying ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science
- Mentor and support the data scientists across multiple projects to drive the development of data science as an AstraZeneca capability
- Review and develop working practices to ensure that data science work is delivered to robust quality standards
- Provide training and advice to project scientists on optimal use of key data, analysis platforms and the appropriate use of biostatistics.
- MSc degree in rigorous quantitative science (such as mathematics, computer science, bioinformatics, computational biology, systems biology)
- Advanced software development skills in at least one of the standard data science languages (such as R, Julia or Python) and familiarity with database systems (e.g. SQL, NoSQL, graph)
- Comfortable working in high performance computing or cloud environment
- Experience of manipulating and analysing large high dimensionality unstructured biomedical datasets, drawing conclusions, defining recommended actions, and reporting results across stakeholders
- Demonstrated scientific knowledge of cell biology, molecular biology, immunology, or biochemistry, especially as it relates to translational science research and development
- Excellent written and verbal communication, business analysis, and consultancy skills
- A passion to apply machine learning to solve difficult problems in drug development
- PhD degree in rigorous quantitative science (such as mathematics, computer science, bioinformatics, computational biology, systems biology).
- Proven track record of publishing relevant bioinformatics or systems biology results and tools in peer-reviewed journals, conferences, and other scientific proceedings.
- Prior experience working in a therapeutic drug research or development. Demonstrated contributions in target discovery, indication discovery, and patient-disease stratification initiatives are highly desirable.
- Experience in novel methods development and application
Possible locations for this role are Cambridge UK, Gaithersburg US or Gothenburg Sweden.
Competitive salary and benefits apply.
Posting date: 29th January 2020
Closing date: 6th March 2020
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.