Data Scientist

Who you are… You’re an early-career data scientist based in the UK who has recently completed a data-heavy Bachelor’s or Master’s with some healthcare focus. You’re now looking for a growth opportunity where you can be a part of innovative healthcare research.    You’ll have some experience cleaning, processing and analysing messy data. You know that only with clean, trustworthy data can we get results that matter. You’re keen to get ‘stuck in’ to not only build the infrastructure for real-world evidence studies but then process and use these data to deliver insights shaping the evidence for cutting edge therapies. Your background could be in clinical or healthcare sciences, biomedical research, or something similar. When we talk about cloud-based data platforms, data pipelines, and statistical analysis plans, you’ll know exactly what we mean (and maybe even get excited!). This is an early career role, so we don’t expect you to be an expert on every tiny detail of modern tech stacks or statistical methodology. However, being keen to learn quickly and being obsessed with quality are non-negotiable. You’ll become a core member of a friendly Analytics team at an exciting time as we blend existing projects with R\&D (read: cool maths) with a ‘start-up within a company’ mentality. What you’ll do… You’ll get involved in a range of activities, but the role will start off as being approximately 2/3 data infrastructure with 1/3 projects and R\&D. Your activities will include: ·         Supporting the management and processing of multi-modal real-world data. ·         Contributing to the development of cloud-based data lakes and data pipelines. ·         Using the infrastructure that you’ve helped build to develop and maintain data dashboards. ·         Working closely with all team members to support the analytical engine that drives RWE generation across all our studies. These need to be on time and on point. ·         Support producing, reviewing, and quality controlling project requirements and other documentation, including statistical analysis plans, data specifications, and study protocols. ·         Publishing study results and contributions to the writing and publishing of scientific presentations. ·         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. ·         Managing your workload, including developing and following process documents that sit within the Analytics team.   Essential skills and experience… ·         BSc or MSc in Statistics, Biostatistics, Data Science, or another demonstrably relevant field. ·         Some understanding of the complexities of real-world health data plus experience handling it.  ·         Solid knowledge of R and Python. ·         High degree of technical competence and effective communication skills, both oral and written. ·         An understanding of common data quality issues. ·         Awareness of privacy, security, and regulatory considerations when working with healthcare data. ·         Possess a logical and methodical approach to troubleshooting data quality issues and code.   Desirable skills and experience… ·         The data stack runs on AWS, so some experience with AWS data lakes (e.g. S3 buckets, Glue scripts) and being keen to learn more would be a bonus. ·         Experience with dashboarding. ·         Experience with SQL. ·         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 heavily regulated environment where transparency and robustness is part of the day-to-day.       Team Analytics Locations Fully remote (UK based) Hours * 100%; flexible hours Applicants must have the unrestricted right to work in the UK . Unfortunately, we are unable to provide visa sponsorship for this position.