At a Glance
- Tasks: Lead analytic workstreams and develop statistical methods for global projects.
- Company: Dynamic company focused on innovative data solutions in healthcare.
- Benefits: Competitive salary, mentoring opportunities, and career progression.
- Other info: Collaborative environment with opportunities to train and mentor junior staff.
- Why this job: Make a real impact in healthcare with cutting-edge technology and global projects.
- Qualifications: BSc/MSc in Statistics/Biostatistics, strong SAS/R skills, and experience with real-world data.
The predicted salary is between 55000 - 70000 £ per year.
As a Data Scientist, you will be given access to cutting‑edge in‑house technology, allowing you to work on global projects across a variety of therapeutic areas. Thanks to our development opportunities and mentoring at all levels, you will be able to progress your long‑term career in the direction you choose.
You will lead analytic workstreams, be involved in the development of statistical methods sections of protocols, prepare statistical analysis plans, and generate analytic results. You will contribute to data management and statistical programming of various data sources and communicate with clients regarding study protocol or statistical analysis issues as they arise.
Key Responsibilities- Serve as a statistical/analytic lead in secondary database studies.
- Work collaboratively with other functional team leads and external clients to deliver analytic results on time, with high quality and within budget.
- Ensure quality control (QC) reviews of Statistical Analysis Plan (SAP) and Shells.
- Write and maintain programming specifications.
- Assist with protocol development and sample size calculations.
- Write and/or QC data management and statistical programming code in R/SAS.
- Build and maintain effective customer relationships, driving statistical discussions, providing support and/or guidance for statistical activities.
- Manage scope of work and budget, and provide revenue and resource forecasts for single studies.
- Train and mentor junior staff.
- Support colleagues and provide motivation as needed.
- BSc or MSc in Statistics/Biostatistics or related field.
- Practical experience working with real‑world secondary databases (e.g., national registries, claims, EMR, etc); practical experience with UK or Nordic national registry data is a plus.
- Strong SAS and R programming skills.
- Ability to understand written documentation of registries.
- CRO and/or pharmaceutical industry experience.
- Strong communication skills in English.
- Ability to manage multiple tasks and deliver high quality outputs within agreed timelines.
Senior Data Scientist, RWE employer: IQVIA
As a Senior Data Scientist at our company, you will thrive in a dynamic work environment that champions innovation and collaboration. With access to state-of-the-art technology and a commitment to employee development through mentoring and training, we empower you to shape your career path while contributing to impactful global projects. Our inclusive culture fosters teamwork and encourages professional growth, making us an exceptional employer for those seeking meaningful and rewarding work in the healthcare sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist, RWE
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We think you need these skills to ace Senior Data Scientist, RWE
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 IQVIA, 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 IQVIA. 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 IQVIA
✨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 IQVIA!
✨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.
