Statistical Consultant

JR United Kingdom; Coventry; Remote; GBP 70,000 - 100,000; Full time

Job summary

A leading company seeks a Statistical Science Associate Director to join their Statistical Innovation group. This remote position involves delivering pragmatic statistical solutions for clinical studies, collaborating with global teams, and leading innovative projects in drug development. Ideal candidates will have a PhD in Statistics and proven expertise in statistical methodologies.

Qualifications

• PhD in Statistics or related field, with experience in clinical drug development.
• Strong programming skills in R and/or SAS.
• Research record with publications in top statistical journals.

Responsibilities

• Provide key insights and solutions in drug development stages.
• Lead strategic projects and develop new methodologies.
• Conduct analysis for clinical studies using advanced methods.

Skills

Statistical methodology support

Collaboration

Programming skills in R

Programming skills in SAS

Innovative statistical solutions

Education

PhD in Statistics

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 impact a company that transforms ideas into life-changing medicines?

At AstraZeneca, we prioritize patients and strive to meet their unmet needs worldwide. We apply cutting-edge science across various business areas. Working here means being entrepreneurial, thinking big, and collaborating to make the impossible possible. If you are proactive, confident in leadership, eager to collaborate, and curious about science, you are our ideal candidate.

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

You will be part of the Respiratory Biometrics and Statistical Innovation department, where data-driven approaches help 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 through quantitative reasoning.

Main duties and responsibilities:

Joining a team of statistical methodology experts, you will provide key insights and find solutions at critical stages of drug development. This role involves technically challenging work in a dynamic landscape. Your main focus will be on delivering pragmatic solutions quickly, then refining them over time.

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 frequentist and Bayesian methods.
• Analysis methods for real-time data, Estimands, Missing Data, Subgroup analyses, and Biomarkers.

You will also serve as an expert consultant to statisticians, medical scientists, and other stakeholders. This includes leading strategic projects, developing new methodologies, engaging with external scientists and regulators through publications and collaborations, and identifying new areas where Statistical Innovation can add value.

Requirements:

• PhD in Statistics or a related field, with experience in academic research and/or clinical drug development.
• Proven ability to deliver innovative statistical solutions in applied settings, particularly in clinical trial 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 with publications in top statistical journals.
• Passion for applying scientific expertise to practical problems benefiting patients.
• Knowledge or research experience in safety data analysis, observational studies, meta-analysis, Bayesian methods, and non-linear/mixed effect models.
• Awareness of evolving scientific and regulatory issues in statistics.