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Location:
Cambridge, England, United Kingdom
Job reference: R-025307
Posted date: Mar. 26, 2019
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Associate Principal Data Scientist

Oncology IMED Biotech Unit

Cambridge, UK

Salary Competitive

At AstraZeneca we turn ideas into life changing medicines. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality.

The vision of AstraZeneca Oncology is to redefine cancer, redefine our solutions to cancer, and restore patients' lives.  The Oncology Bioinformatics group work within cross-disciplinary drug project teams, specializing in genomics (next generation sequencing, NGS) and multi-omic data analysis to drive new target discovery, pre-clinical and clinical research and precision medicine. 

Excitingly the group is expanding to harness diverse data science within our research, spanning probabilistic and mathematical modelling techniques, machine learning, knowledge graphs and other flavors of artificial intelligence (AI).  We have a fantastic opportunity for a talented mathematically trained individual to become technical leader for machine learning and drive innovation in our portfolio.

Main Duties and Responsibilities:

You will interact with drug project bioscience and translational science teams to understand their data and identify new areas to apply machine learning solutions to their scientific challenges.  You will work alongside domain experts in bioinformatics and genomics to benchmark and optimize algorithms and models, maximizing impact and insight.  You will influence IT and informatics groups to optimize underlying data infrastructure.

Projects and algorithm development will be directed towards machine and deep learning for:

  • Feature engineering/extraction for genomics, CRISPR, and phenotypic assays.
  • Integration of prior knowledge with multi-layered patient data for precision medicine.
  • Pattern recognition, feature selection and casual inference in NGS and multi-omic data.

As a lead data scientist in oncology research you will maintain awareness of stat-of-the-art applications of machine learning and engage leadership to design and influence strategic decisions.  You will identify and lead external interactions with opinion leaders in the field and grow our external reputation by publishing innovative methodologies and scientific discoveries.

You will be supervising and mentoring data scientists, directing their day-to-day scientific and technical delivery, as well as influencing and training all members of the bioinformatics team to effectively use machine learning.  You will educate the AZ Oncology community to recognize opportunities for machine learning and adopt a data-first FAIR culture.  You will be firmly engaged with the burgeoningdata science community across AZ to transfer learning and establish best practices, sharing code and peer insight.

Minimum Requirements:

  • Motivated to use state-of-the-art approaches to find meaning in complex/big data for health.
  • Education to graduate degree in a quantitative discipline (Applied Statistics, Computational Statistics, Mathematics, Data Science, Physics, or similar), plus subsequent positions applying data science to research or industry.
  • Expert solving complex data problems with a broad set of machine learning techniques including neural networks, and skilled at fitting the right method to a problem.
  • Programming proficiency with Python or R; version control (Git/Bitbucket).
  • Experience with techniques that enhance utility of representational learning (including deep learning) for biological data e.g. fixing prior knowledge, logic reasoning, transfer learning, graph techniques, attention mechanisms, reinforcement.
  • Strong collaborator skilled in effective communication of complex methods to a non-expert.
  • Impact recognized through publication.
  • Desired but not essential: Experience working with biological or health data e.g. genomics.
  • Desired but not essential: An understanding of the molecular drivers of human diseases.

Next Steps – Apply today!

Applications Open 26th March 19

Applications Close 25th April 19

AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, gender or gender orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.

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Associate Principal Data Scientist, Oncology
Scientific

AstraZeneca in the UK

Our 6,700-strong UK workforce is based across seven sites in the UK, including our new research facilities and global corporate headquarters in Cambridge. The Cambridge Biomedical Campus (CBC) is globally renowned as a leading centre of research, education and patient care. For AstraZeneca, the campus is the perfect environment in which to foster a vibrant culture of open innovation and collaboration.

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