Senior Data Scientist - Digital Health

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Data Scientist, Digital Health

Cambridge UK, Gothenburg SWE, Gaithersburg US

Competitive Salary + Benefits

Make a more meaningful impact to patients’ lives around the globe

Here you’ll have the chance to create a meaningful difference to patients’ lives. With science at its heart, this is the place where breakthroughs born in the lab become transformative medicines – for the world’s most complex diseases.

Answer unmet medical needs by pioneering the next wave of science, focusing on outcomes and shaping the patient ecosystem. With our ground-breaking pipeline, the outlook is forward-thinking.

Be proud to be part of a place that has achieved so much, yet is still moving forward.

There’s no better time to join our global, growing enterprise as we own the way for healthcare and society.

A place that’s investing in the latest technology, data and innovative ways of working. Here you’ll be backed with everything you need to be at the forefront of digitising our organisation. Whether that’s working on the leading-edge, defining the future of Pharma or upskilling yourself in our Digital and Data Academy.

Responsibilities

We work on a flexible and multifaceted portfolio of challenges that include, but are not limited to:

• Enabling Digital Health by developing an ecosystem of data science capabilities for improved clinical trial design, execution and monitoring that includes remote monitoring, telemedicine, medical and wearable devices to augment trials
• Researching and developing data science algorithms using high-frequency data generated from trials to achieve goals on patient centricity and improved clinical trial design/execution
• Developing and implementing end-to-end automation and integration of our algorithms in products using state-of-the-art serverless architectures in cloud platforms such as AWS
• Supporting individual therapeutic areas and study teams solve varied challenges using statistics, data sciences and machine learning

These challenges will require you to:

• Lead, advise on, investigate the feasibility of, and deliver data science solutions and ideas 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, sophisticated business problems into the appropriate data problem, model and analytical solutions
• Develop, implement and maintain tools and algorithms in a manner which meets regulatory and evidential requirements
• Clearly and objectively communicate results, as well as their associated uncertainties and limitations
• Constructively collaborate with a diverse set of users (global functions and local marketing companies) and partners enabling effective consensus, conflict resolution and alignment to project goals
• Review and develop working practices to ensure that data science work is delivered to robust quality standards

Essential:

• PhD/MS in mathematics, computer science, statistics, physics, engineering or a related computational subject area. Applicants who also have proven experience in data science and high proficiency in predictive modelling are encouraged to apply.
• High proficiency and proven track record of researching, designing, coding and delivering high impact data-led insights through machine learning.
• High proficiency in hands-on computer programming in Python, R or similar programming language.
• High proficiency in exploratory data analysis, data profiling and feature engineering on large, structured and unstructured datasets.
• Excellent written and verbal communication, business analysis, and consultancy skills
• Customer focus - dedicated to meeting the expectations and requirements of internal and external customers
• Integrity and trust -- unwavering dedication to doing the right thing
• A passion to apply machine learning and other data science techniques to tackle difficult problems in drug development, clinical trials and related biomedical domains of value for AstraZeneca.

Desirable:

• Experience in novel methods development and application
• Understanding of life sciences, with a preference for clinical drug development and the pharmaceutical environment
• Experience in data-led solution delivery and software lifecycle development practices including Agile/Scrum, Waterfall, DevOps and/or CI/CD.
• Experience in AWS and building serverless data pipelines and inference pipelines.
• Multiple published papers and/or patents, contribution to open source projects

So, what’s next?