Do you have expertise in, and passion for, Data Engineering? Would you like to apply your expertise to impact Data Engineering in a company that follows the science and turns ideas into life changing medicines? Then AstraZeneca might be the one for you!
At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.
Job Description
The Digital Health Oncology Data Science Team aims to transform the patient experience and clinical trial process. We will do so by deploying digital solutions to clinical trials and in the real world to decrease patient burden. The approach the team takes will incorporate clinical trial data, Real World Evidence (RWE) data, clinical free text, medical imaging, Patient Reported Outcomes (PROs), and device data to define new digital approaches to addressing the pressing problems in Oncology.
The team is looking for a Senior Data Engineer to work with the data science team to reduce patient burden through efficiently leveraging clinical trial data, medical imaging data, RWE data and device data. The Data Engineer role will work closely with Data Scientists to develop data models and pipelines to characterize data, clean data and deliver insight to the team regarding data quality. From an engineering and diversity of data perspective, this team will offer the exciting opportunity to integrate multiple types and sources of clinical data with the challenge of developing novel approaches to leveraging the data for machine learning. As the Data Engineer is working closely with the Data Scientists and project engineers, it is also expected to be a growth opportunity with respect to machine learning and engineering skills.
Examples of projects the team works on include machine learning models for developing digital biomarkers, patient risk stratification for clinical trials, new algorithms for survival analysis, approaches to quantitatively analyze wearable data, linking of medical imaging data with 'omics and longitudinal outcomes to identify and/or validate new drug targets, and much more!
Typical Accountabilities
Delivers high-quality and appropriate data to data science team members, appropriately communicating with non-technical stakeholders and data scientists.
Works within established frameworks to deliver a variety of tasks that support projects in meeting their objectives.
Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
Reviews working practices and ensures non-compliant processes are escalated
Ensures own work is compliant within Clinical Development.
Collaborate in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
Work closely and collaborate with key partners and data sources
Build the infrastructure required for efficient extraction, transformation, and loading of data from a wide variety of data sources
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build and maintain efficient data pipeline architecture
Build data tools for data scientists
Education, Qualifications, Skills and Experience
Essential
BSc degree in rigorous quantitative science (such as mathematics, computer science, engineering)
Practical software development skills in standard data science tools: Python, Agile, Code versioning (bitbucket/git), UNIX skills
Experience with clinical trial or EMR data (cleaning, modeling, ontologies or controlled vocabularies).
Minimum 2+ years of industry experience.
Desirable
MSc degree in rigorous quantitative science (such as mathematics, computer science, engineering)
Experience within the pharmaceutical industry
Communication, business analysis, and consultancy.
AWS experience: provisioning resources required for data cleaning & modeling, infrastructure as code is a bonus
Experience creating multi-stage data preprocessing pipelines
Prior experience with ontologies or controlled biomedical vocabularies is a plus.
Why AstraZeneca?
At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognizing their potential. Join us on our journey of building a new kind of organization to reset expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together. Interested? Come and join our journey.
So, what's next?
Are you already imagining yourself joining our team? Good, because we can't wait to hear from you.
Where can I find out more?
Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
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