Senior Statistician - Statistical Innovation

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Job description

Senior Statistician - Statistical Innovation, BioPharmaceuticals Biometrics

Description

Do you have a passion for developing and aiding implementation of innovative statistical approaches and methods in clinical studies? Are you up for the challenge to impact a company that follows the science and turns ideas into life changing medicines? If yes, we welcome you to join AstraZeneca!

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide, while applying leading edge approaches to science across many business areas. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to act, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.

We are recruiting a Senior Statistician to join our growing Statistical Innovation group. Our main focus is providing statistical methodology support for all phases of clinical development for AZ's Cardiovascular, Renal & Metabolism and Respiratory & Immunology divisions together with specific targeted support for the Oncology division and the newly acquired Alexion division of AZ which specializes in medicines to treat rare diseases.

In this role, you will belong to the Early Biometrics & Statistical Innovation (EB&SI) department, where our data-centric focus helps us work efficiently and creatively to bring the right medicines to the right patients. Our teams use their expertise in statistics and programming to address drug development objectives and reduce uncertainty in product development, driving better business decisions with quantitative reasoning. As part of the Data Science & AI team, you'll use technology at the forefront of science in a creative environment, with the scope to develop new statistical ideas and apply them in your work.

Main duties and responsibilities

Joining a team of statistical methodology experts, you will provide key input as you work to find solutions to problems at critical stages in the drug development cycle. This is exciting and technically challenging work in a dynamic and constantly changing landscape. Your key focus will be on producing pragmatic solutions, often within a tight time scale where the emphasis will be to deliver first, then refine and develop your solutions thereafter.

You will contribute to one of the following statistical areas:

• Design of early and late phase clinical studies: including group sequential and adaptive designs using both frequentist and Bayesian approaches.
• Methods to analyse data collected in real-time, Estimands, Missing Data, Subgroup and Biomarkers.

You will also provide expert consultancy on key issues for fellow statisticians working in our therapeutically aligned statistics groups, as well as medical scientists and other key roles across the business. This will involve participating in strategic activities such as capability build projects, which can directly impact improvements to the way clinical trials are designed and analysed in AstraZeneca. As well as developing and implementing new methodology, interacting with external scientists and regulators, through publications, presentations and cross-industry collaborations. There will also be a focus to proactively identify new areas where Statistical Innovation can add value, developing collaborative relationships with the external scientific/academic community.

Essential Requirements

• MSc or PhD in Statistics or a related discipline.
• Experience of independent academic research and/or clinical drug development including knowledge of statistical methodological methods used in the design and analysis of early and late Phase clinical trials.
• Strong knowledge of programming in R and/or SAS
• An urge to apply your scientific competence on practical problems, for the benefit of patients

Desirable Requirements

• A track record of research and methodological development in Statistics, supported by scientific publications
• Knowledge / research experience in the development of statistical methodology related to the analysis and interpretation of safety data, observational studies, meta-analysis, non-linear and mixed effect models.
• Broad awareness of statistical issues against the evolving scientific, regulatory & payer landscape

Why AstraZeneca?

It's a place to think differently - to find new ways of handling and treating diseases. We are trusted and empowered to explore. Ultimately, it's more than a job. We know that our work impacts people with serious conditions, many of whom have no other alternatives. That's what drives us - the potential to impact over one billion patients worldwide.

AstraZeneca has taken critical steps to protecting colleagues, loved ones, and patients from COVID-19 and its variants. COVID-19 vaccination is required for all US employees, and weekly PCR COVID-19 testing is required for those who are unvaccinated or have an approved accommodation.

So, what's next! If this sounds like your next challenge - apply today! We look forward to get to know you better. Welcome to send us your application through our website at your earliest convenience, but no later than

Where can I find out more?

Follow AstraZeneca on LinkedIn:

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Read more about BioPharmaceuticals R&D:

Our dedicated Biometrics landing page is:

#DataAI

Date advert opened: 11th October 2021

Date advert expires: 11th November 2021

Date Posted
11-Oct-2021

Closing Date
12-Dec-2021

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.