Statistical Science Associate Director - Statistical Innovation

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

Statistical Science Associate Director – Statistical Innovation, BioPharmaceuticals Biometrics

Location: Cambridge or Macclesfield (UK) Gaithersburg, Waltham, Durham or Wilmington (US) Gothenburg (Sweden)

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 Statistical Science Associate Director 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, or lead capability build in more than 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 leading and 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.

Requirements

Essential

• PhD in Statistics or a related discipline, followed by experience of independent academic research and/or clinical drug development
• Documented ability of delivering innovative statistical solutions in an applied environment (related to at least one of the following areas: Design of early and late phase clinical studies: including group sequential and adaptive designs. Analysis of data collected in real-time (e.g. sensor data), Missing data and Estimands, Subgroups and Biomarkers)
• Strong knowledge of programming in R and/or SAS
• High level of competence in global and cross-skilled collaborative working
• Track record of research and methodological development in Statistics, supported by scientific publications in first class statistical journals
• Desire to apply your scientific competence on practical problems, for the benefit of patients

Desirable

• Knowledge / research experience in the development of statistical methodology related to the analysis and interpretation of safety data, observational studies, meta-analysis, Bayesian statistics, non-linear and mixed effect models.
• Broad awareness of statistical issues against the evolving scientific and regulatory landscape