Research Data Scientist, Early Oncology R&D

  • AstraZeneca
  • Cambridge, England, UK
  • 23/04/2019
Full time Data Science Data Engineering Machine Learning Data Analytics Artificial Intelligence Data Management Statistics Software Engineering

Job Description

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.  Every single day, we make a difference by delivering potentially life-changing medicines to millions of people worldwide.  

We are passionate about the power of data and Artificial Intelligence (AI) as a catalyst for change.  We are transforming to deliver a FAIR science data foundation, AI-augmented drug design and genomics, knowledge graphs driving biological insights and holistic precision medicine.  Join AstraZeneca Oncology’s vision to redefine cancer, redefine our solutions to cancer, and restore patients' lives. 

Minimum Requirements:

  • BSc and MSc or PhD degrees in a quantitative discipline (Applied Statistics, Mathematics, Data Science, Physics or similar).
  • Relevant work experience, including full time industry experience or post-doctoral research.
  • Expert solving complex data problems with a broad set of machine learning and statistical data mining techniques, including deep learning.
  • Experience with machine intelligence, algorithmic foundations of optimization, transfer learning, graph techniques, machine attention or reinforcement learning.
  • Programming proficiency with Python or R; version control (Git/Bitbucket).
  • Experience contributing to the research community through publication and conferences.
  • Experience working with biological or health data e.g. genomics.

About the job

In AstraZeneca Oncology our data scientists are embedded throughout our research organization.  As a Research Data Scientist, you will work alongside drug project bioscientists, software engineers and bioinformaticians to generate new ideas to impact our science with machine learning.  We will provide an environment where you can collaborate with domain experts and the burgeoning data science community to create experiments, steer data generation and rapidly deploy solutions. 

Typical research will focus on applying machine intelligence, natural language processing and deep learning for:

  • Feature engineering/extraction for genomics, CRISPR, and phenotypic assays.
  • Representation and modeling of multi-modal patient data for precision medicine.
  • Retrieving and harnessing prior-knowledge to augment machine intelligence.

The team will actively research ways in which to improve machine learning algorithms and infrastructure for biological data and enable practical application by our research community.  You will maintain awareness of cutting-edge applications of machine learning and initiate collaborative interactions with leaders in the field.  You will grow your external reputation and contribute to the wider research community by publishing innovative methodologies and scientific discoveries.

You will have the opportunity to supervise and mentor junior data scientists, directing their day-to-day scientific and technical delivery.  You will educate the AZ Oncology leadership and scientific community to recognize opportunities for machine learning and adopt a data-first FAIR culture.