Senior Real World Data Scientist

This is what you will do:

The Epidemiology and Real World Science team is a growing group within Alexion-AstraZenca Rare Disease Unit which is driving the scientific use of Real World Data to accelerate the way that patients access innovative medicines.  In this role, you will focus on Real World Data applications supporting the rare disease portfolio, while maintaining alignment with AstraZeneca best practices and standards.AstraZeneca has a rich history in Real World Evidence, having developed a coherent strategy to develop and internalize data assets the group is now amplifying those investments through a dedicated Real World Data Science capability. Real World Data Scientists who are successful in this role will work on challenging problems, using innovative approaches to accelerate the delivery of Real World Insights and Evidence for key internal and external stakeholders with an emphasis on Clinical Development, Regulatory, and Patient Safety applications.

The ideal candidate for this role will be a curious, self-learner and bring a proven track record of delivering value from routinely collected data from healthcare settings or observational studies to provide health analytics and insights in a range of contexts including Public Health, Pharmaceutical Research and Development and Commercial/ Payer and Patient Safety.

They will provide methodsexpertise and support delivery of a range of analyses of real world data to support the business and give expert scientific and technical guidance on study design, RW data selection and best practice in RW data utilization with emphasis on patient safety. 

In addition, they will assist in advancing and shaping Alexion and AZ’s Real World Science data strategy through supporting  due diligence on new data providers/vendors, informatics support for data acquisitions for Therapeutic Areas.

You will be responsible for:

• Deliver/Implement and support advanced secondary analyses of data from EMR, claims and primary observational data required by Therapeutic Area (TA) RWE strategies

• Comfortable working in a rapid analytics environment alongside stakeholders to ideate appropriate/impactful analysis along with implementation

• Provide clear technical input, options and directions to support strategic decisions made by AZ observational study teams on study design, data partner selection and best practices in RWE data utilization

• Monitor work performed by contract personnel and vendors 

• Maintain a strong insight into the capabilities of potential external partners in RWE, especially for US and emerging markets.

• Demonstrate best practice in Real World Data Science across multiple domains, and/or stakeholder groups.

You will need to have:

• Minimum of Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related field with at least 3 years in the pharmaceutical industry, biotechnology, or consulting environment. 

• The duties of this role are generally conducted in an office environment.  As is typical of an office-based role, employees must be able, with or without an accommodation to: use a computer; engage in communications via phone, video, and electronic messaging; engage in problem solving and non-linear thought, analysis, and dialogue; collaborate with others; maintain general availability during standard business hours.

We would prefer for you to have:

• This is a hands on role – sobeexcited to code!

• Enthusiastic about building on and learning new methods and ways to use real world data to change the practice of medicine

• Demonstratedability to build long-termrelationshipswithstakeholders ,understand relevant scientific/business challenges at a deeplevel and translate into a programme of data science activities to deliver value to the business

• Hands-on experiencewith EMR/Health IT, diseaseregistries, and/or insurance claims databases

• Experiencewith in clinical data standards, medical terminologies and controlledvocabulariesused in healthcare data and ontologies (ICD9/10/SNOMED)

• Experience in supportingpharmacoepidemiologystudieswithproventrack record of advancingapproacheswithstatistics/machine learning/data science

• Ability to lead & manage multi-disciplinary data science projects

• Proficient in SQL 

• Proficient in at least one of R, Python or SAS