Statistician

JR United Kingdom; Preston; On-site; GBP 25,000 - 35,000; Full time

Job summary

A leading company in healthcare research seeks an early-career statistician proficient in R, with knowledge in data analysis and management. This role involves working on diverse, impactful projects in a dynamic environment, supporting data-driven decision-making in clinical research. Candidates with a strong academic background and a passion for learning will thrive in this role.

Qualifications

• Proficiency in R with knowledge of data analysis & management.
• Experience in managing research datasets and data manipulation.
• Interest in real-world studies and patient-focused research.

Responsibilities

• Support analytics across studies, collaborating with the Director.
• Manage data processing and quality control documentation.
• Contribute to the development of scientific dashboards.

Skills

R

Data analysis

Statistical programming

Data management

Education

MSc or PhD in Statistics, Biostatistics, Data Science

Tools

SQL

Python

Java

Job description

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You’re an early-career statistician who’s proficient in R, a working knowledge of data analysis and management solutions such as Python and SQL would be ideal.

Your background is in clinical, healthcare, health services, or pharmaceutical research background, and when we talk about the intricacies of statistical analysis plans and quality control logs, you’ll know exactly what we mean. But this is an early-career role: we aren’t expecting you to be an expert on every little statistical thing. You want this role because of how much you’ll learn very quickly.

You’ve got some experience in managing research datasets, ideally complex ones. This has given you the necessary knowledge about data manipulation and statistical analyses, data quality checking and cleaning, and working in a data management setting.

You’ve got an interest in real-world studies and patient-focused research projects that involve collecting data from patients and carers as well as clinical data. You like working on exciting, diverse projects that involve cutting-edge technology…and a lot of creative thinking as a result.

What you’ll do…

You’ll get involved in a range of activities, including:

·Working closely with the Director and Statistical Lead to support the analytics across all of our studies.

·Being a go-to person for data management and processing, providing technical and analytical expertise.

·Providing support for producing, reviewing, and quality controlling project requirements and other documentation, including statistical analysis plans, data specifications, data platform configuration, study protocols as well as result dissemination in final reports and other deliverables.

·Publishing results of studies and contributing to the writing and publishing of scientific presentations.

·Providing support and contributing to the development of scientific dashboards

·Providing support for technical audits and ensuring continued compliance with required company training, time reporting, and other business/operational processes.

·Ensuring all Analytics team processes are followed, with the view of all work being auditable and suitable for regulatory submissions.

·Keeping on top of developments in data technologies, analytics, methods, and systems.

·Being knowledgeable about data protection issues.

·Being able to write software programs, for example, to extract data from databases and to clean data (using SQL, R, Python, Java).

·Managing your workload, including developing and following process documents that sit within the Analytics team.

Essential skills and experience…

·MSc or PhD in Statistics, Biostatistics, Data Science, or another demonstrably relevant field.

·Proven knowledge of the R environment.

·Demonstrated high degree of technical competence and effective communication skills, both oral and written.

Desirable skills and experience…

·1+ years of experience

·Good knowledge of any of the following:

·Experience-based knowledge of the pharmaceutical industry, directly or through, e.g., academic roles, or roles with developers, manufacturers, or in consulting, and related evidence development.

·Knowledge of experimental and real-world evidence study design, descriptive statistics, inferential statistics, statistical modeling, and statistical programming.

·Knowledge of methodologies for handling missing data, confounding, and bias, among other challenges, within observational studies.

·Experience of working in a regulatory setting.