Senior Statistical Analyst

Senior Statistical Analyst

Full-Time 54000 - 66000 £ / year (est.) Hybrid
I

At a Glance

  • Tasks: Join our team to analyse real-world data and support healthcare decision-making.
  • Company: ICON, a global leader in healthcare intelligence and clinical research.
  • Benefits: Competitive salary, health coverage, retirement plans, and career development opportunities.
  • Other info: Collaborative environment with opportunities for growth and knowledge sharing.
  • Why this job: Make a real impact on patient outcomes through innovative research projects.
  • Qualifications: Master's or PhD in a quantitative field with strong SAS programming skills.

The predicted salary is between 54000 - 66000 £ per year.

JR158816 Senior Statistical Analyst

ICON is a global healthcare intelligence and clinical research organisation united by a mission to bring new medicines and treatments to patients faster.

As a values-driven organisation, integrity, collaboration, agility, and inclusion are at the heart of how we work and interact with each other, customers, patients and suppliers.

Senior Statistical Analyst - Real World Evidence

We are currently seeking a Senior Statistical Analyst to join our Real World Evidence (RWE) team.

This position offers an exciting opportunity to work on observational research studies, real-world data analyses, health outcomes research, and epidemiology projects that help generate evidence to support healthcare decision-making.

As a Senior Statistical Analyst, you will play a key role throughout the project lifecycle, from study design and statistical planning through to analysis, reporting, publication and client interaction.

The role requires strong technical expertise in SAS programming, statistical methodology, and the interpretation of complex healthcare datasets.

  • What You Will Be Doing
  • Support study conception, design, and protocol development for real-world evidence and observational research projects.
  • Contribute to study start-up activities, including review and development of protocols, case report forms, and statistical methodologies.
  • Write statistical methods sections of study protocols and develop statistical analysis plans.
  • Perform sample size and power calculations.
  • Review database specifications and participate in data review activities.
  • Develop table, listing and figure shells and programming specifications.
  • Lead the review and validation of raw and derived variables.
  • Create and maintain derived datasets using SAS programming.
  • Conduct statistical analyses using appropriate methodologies, including advanced and specialized statistical techniques such as longitudinal analyses, repeated measures, survival analyses, and other complex modelling approaches.
  • Develop and validate SAS programs, macros, tables, listings, figures, and project deliverables.
  • Lead quality control activities throughout programming and analysis processes.
  • Manage and review internal and external data transfers.
  • Produce project reports, statistical outputs, visualizations, tables and graphs for client delivery.
  • Contribute to manuscripts, abstracts, conference presentations and peer-reviewed publications.
  • Write methods and results sections for final reports and scientific publications.
  • Communicate directly with clients, investigators and cross-functional teams regarding project deliverables and statistical requirements.
  • Represent Statistical Analysis in proposal development and RFP activities.
  • Participate in department initiatives, process improvements, SOP development and training activities.
  • Deliver internal technical presentations and contribute to knowledge sharing within the team.
  • Attend departmental meetings and support broader Real World Evidence research activities.

Your Profile

To be successful in this role, you will possess a strong statistical and programming background, together with experience working with healthcare, clinical, observational or real-world data.

Required Qualifications and Experience

  • Master's degree or Ph D in Statistics, Biostatistics, Epidemiology, Mathematics, Data Science, Public Health, or a related quantitative discipline.
  • Significant experience within the pharmaceutical, biotechnology, CRO, healthcare research, or Real World Evidence environment.
  • Advanced SAS programming experience is essential, including development of datasets, statistical analyses, macros, tables, listings and figures.
  • Strong understanding of statistical methodologies and their practical application to healthcare and observational data.
  • Experience developing Statistical Analysis Plans (SAPs) and analysis specifications.
  • Knowledge of observational study design, epidemiology, health outcomes research, registries, claims databases, electronic health records, or other real-world data sources is highly desirable.
  • Experience applying statistical techniques such as regression modelling, survival analysis, repeated measures analysis and other advanced methods.
  • Ability to independently manage statistical deliverables while collaborating effectively within multidisciplinary teams.
  • Strong written and verbal communication skills with the ability to explain complex statistical concepts to both technical and non-technical audiences.

• Preferred Experience

  • Experience within a Real World Evidence, Health Economics & Outcomes Research (HEOR), Epidemiology, or Data Analytics team.
  • Experience authoring publications, abstracts, or conference presentations.
  • Proficiency in additional programming languages such as R is advantageous.

Why Join the Real World Evidence Team?

You will be part of a collaborative team delivering high-impact research that helps shape healthcare decisions and improve patient outcomes globally.

This role provides the opportunity to work on diverse, scientifically rigorous projects while developing deep expertise in real-world data, advanced analytics and evidence generation.

Please note: Strong SAS programming experience is a core requirement for this position and will be a key focus throughout the selection process.

#LI-SA1

Employment with ICON is contingent upon having the legal right to work in the country where the role is based.

Rewards & Benefits

ICON offers a competitive and comprehensive total rewards package designed to support your health, wellbeing, and career development.

Benefits may include

  • Competitive base salary and performance related incentives
  • Health and wellbeing programmes including medical, dental, and vision coverage where applicable
  • Retirement and pension plans
  • Life assurance and disability coverage
  • Employee assistance programmes and wellbeing resources
  • Learning and development opportunities through structured training and career pathways

Benefits may vary depending on role and location.

Visit our careers site to read more about the benefits ICON offers.

Inclusion and Accessibility

ICON is an equal opportunity employer. We are committed to building an inclusive and accessible workplace where everyone feels valued and supported.

If you require reasonable accommodations during the recruitment process, please let us know or submit a request here

Are you a current ICON Employee? Please click here to apply

Senior Statistical Analyst employer: IRE

ICON is an exceptional employer that prioritises integrity, collaboration, and inclusion, making it a fantastic place for professionals in the healthcare intelligence and clinical research field. With a strong commitment to employee wellbeing, ICON offers a competitive rewards package, comprehensive health programmes, and ample opportunities for career development, all while fostering a diverse and dynamic work culture. Whether working from home or in the office, employees are empowered to manage complex projects and contribute meaningfully to advancing patient-centric outcomes.

I

Contact Details:

IRE Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Statistical Analyst

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like IRE!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Statistical Analyst at IRE.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like IRE.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Statistical Analyst at IRE, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Statistical Analyst

SAS Programming
Statistical Methodology
Data Analysis
Statistical Analysis Plans (SAPs)
Epidemiology
Health Outcomes Research
Observational Study Design

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at IRE, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at IRE. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at IRE

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at IRE!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.