At a Glance
- Tasks: Create innovative R solutions for data analysis in clinical trials.
- Company: Leading pharma company focused on data-driven solutions.
- Benefits: Attractive salary, flexible working options, and continuous learning opportunities.
- Other info: Collaborative global team with a focus on professional growth.
- Why this job: Join a team that drives innovation in clinical data analysis and makes a real difference.
- Qualifications: 5+ years in pharma/biotech, strong R programming skills, and experience with clinical data.
The predicted salary is between 60000 - 80000 £ per year.
The R Technical Solutions Programmer is responsible for implementing the vision for data and analysis infrastructure platforms and other technical solutions to support the data flow from data collection to data submission. Using expertise in R programming and clinical trials to create solutions that will enable an open-source ecosystem for programming. This role will coordinate gathering and prioritizing requirements in the process of design and delivery of fit-for-purpose data and analysis technical solutions.
Responsibilities:
- Collaborates with internal teams to understand requirements and develop processes, tools and utilities that will improve quality and efficiency.
- Develops reusable and robust R package code and/or utilities, along with detailed training/documentation.
- Promotes technical innovation to drive the development of data analysis and visualization solutions within a clinical data environment.
- Partners with study teams in use and further improvement of processes and tools.
- Facilitates change management activities and training for department systems and processes.
Qualifications:
- Minimum 5 years’ industry experience (Pharma, Biotech, CRO).
- Experience with R within regulated clinical development environments.
- Strong R data manipulation and analysis skills using standard tidyverse packages.
- Strong R visualization skills for use in static outputs and dashboards.
- Experience with developing R packages including proper documentation and testing.
- Experience developing SAS code including SAS/MACRO preferred.
- Familiarity with Posit products including Workbench, Positron, and Connect.
- High attention to detail including proven ability to manage multiple, competing priorities.
- Familiarity with drug development life cycle and experience with manipulation, analysis, and reporting of clinical trials’ data.
- Ability to work effectively and successfully in a globally dispersed team environment with cross-cultural partners.
Senior R Statistical Programmer employer: Cytel
Cytel is an exceptional employer that fosters a collaborative and innovative work culture, particularly for Biostatisticians dedicated to advancing Chemistry, Manufacturing, and Control (CMC) projects. With a strong emphasis on employee development, you will benefit from consistent training and support while working closely with a global pharmaceutical client at the forefront of patient treatment. This role offers the unique opportunity to contribute to meaningful projects in a dynamic environment where your expertise in Bayesian analysis can truly make an impact.
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We think this is how you could land Senior R Statistical Programmer
✨Get Involved in Data Science Meetups
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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 Cytel.
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We think you need these skills to ace Senior R Statistical Programmer
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 Cytel, 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 Cytel. 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 Cytel
✨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 Cytel!
✨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.
