Statistical Consultant

JR United Kingdom; West Midlands Combined Authority; Remote; GBP 75,000 - 110,000; Full time

Job summary

A leading company seeks a Statistical Science Associate Director to innovate in clinical studies. The role emphasizes collaboration, statistical methodology support, and delivering pragmatic solutions. Ideal candidates will have a PhD in Statistics and experience in clinical drug development, coupled with strong R/SAS programming skills.

Qualifications

• PhD with experience in clinical drug development.
• Proven ability to deliver innovative statistical solutions.
• Strong programming skills in R and/or SAS.

Responsibilities

• Provide key input in drug development cycle phases.
• Lead projects on clinical study design and statistical methodology.
• Engage with scientists and regulators through publications.

Skills

Statistical solutions

Clinical study design

Real-time data analysis

Programming in R

Programming in SAS

Collaborative skills

Statistical methodology

Education

PhD in Statistics or related discipline

Job description

Role: Statistical Science Associate Director – Statistical Innovation

Location: Remote

Duration: 12 months

Description:

Are you passionate about developing and implementing innovative statistical approaches in clinical studies? Do you want to make an impact by contributing to a company that transforms ideas into life-changing medicines?

At AstraZeneca, we prioritize patients and aim to meet their unmet needs worldwide by applying cutting-edge science across various areas. Working here means being entrepreneurial, thinking big, and collaborating to turn the impossible into reality. If you are proactive, confident in leadership, collaborative, and curious about science, you might be a great fit.

We are hiring a contractor to join our growing Statistical Innovation group as a Statistical Science Associate Director. Our main focus is providing statistical methodology support across all phases of clinical development for divisions including Cardiovascular, Renal & Metabolism, Respiratory & Immunology, Oncology, Rare Diseases, and Vaccines.

You will be part of the Respiratory Biometrics and Statistical Innovation department, where our data-driven approach helps us work efficiently and creatively to deliver the right medicines to the right patients. Our team uses expertise in statistics and programming to address drug development challenges and reduce uncertainty, enabling better business decisions with quantitative reasoning.

Main duties and responsibilities:

Joining a team of statistical methodology experts, you will provide key input and solutions at critical stages in the drug development cycle. This work is technically challenging and dynamic, requiring pragmatic solutions often within tight timelines, focusing on delivering first, then refining them.

You will contribute to or lead capability building in areas such as:

• Design of early and late-phase clinical studies, including group sequential and adaptive designs using both frequentist and Bayesian approaches.
• Methods for analyzing real-time data, Estimands, Missing Data, Subgroups, and Biomarkers.

You will also provide expert consultancy to statisticians, medical scientists, and other stakeholders across the business. This includes leading strategic projects, developing new methodologies, engaging with external scientists and regulators through publications and collaborations, and proactively identifying new areas where Statistical Innovation can add value.

Requirements:

• PhD in Statistics or related discipline, with experience in academic research and/or clinical drug development.
• Proven ability to deliver innovative statistical solutions in applied settings, including clinical study design, real-time data analysis, Missing Data, Estimands, Subgroups, and Biomarkers.
• Strong programming skills in R and/or SAS.
• Excellent collaborative skills across global teams.
• Research record supported by publications in top statistical journals.
• Desire to apply scientific expertise to practical, patient-benefiting problems.
• Knowledge in statistical methodology for safety data analysis, observational studies, meta-analysis, Bayesian methods, and non-linear/mixed models.
• Awareness of evolving scientific and regulatory issues in statistics.