This is an exciting opportunity for an experienced Data Scientist to be part of an initiative that works on innovative, complex projects to improve audit reporting to drive national quality improvement and clinical research to assess treatment, outcomes and operations. The successful candidate will be a keen problem-solver and a team-player, and will demonstrate that they can formulate inventive solutions to technological challenges.
The Sentinel Stroke National Audit Programme (SSNAP) is a national healthcare quality improvement programme based in the School of Life Course and Population Sciences at King’s College London. SSNAP measures both the processes of care (clinical audit) provided to stroke patients, as well as the structure of stroke services (organisational audit) against evidence-based standards. In total, over the last 8 years since 2013, almost 700,000 cases have been recorded.
The postholder will be part of a highly collaborative and inclusive team. Proficiency in the use of programming tools for data and database manipulation is essential. Applicants will have a strong interest in and knowledge of clinical research data, a proactive attitude, and excellent organisational and planning skills.
This post will be offered on a fixed-term contract until 31 March 2023.
This is a full-time post – 100% full time equivalent
• You will work closely with the SSNAP manager to develop new tools and processes to streamline and upgrade clinical reporting to provide insights which will help improve patient care
• You will use your Python skills to help SSNAP meet its many reporting requirements
• You will be expected to learn new concepts and quickly build proficiency to test the applicability of new models and tools
• A large part of your role will also be supporting academic and clinical stakeholders in the wider stroke programme to analyse data, design visualisations and supplement written reports for NHS strategy, and preparing conference presentations and journal publications
• As a custodian of SSNAP data, you will be responsible for ensuring quality outputs by developing and implementing test strategies
• You will be a point of contact to clarify any queries from the wider team regarding data quality assurance and you will be expected to document processes to improve technical and non-technical user understanding of data collection, analysis, and interpretation of results.
• You will handle personal information responsibly, adhering to safe and secure data governance, in line with protocols and current data protection legislation
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Skills, knowledge, and experience
1. Graduate degree (BSc or MSc) in a computing/engineering subject OR equivalent industrial experience in data science/software development
2. Experience contributing to large data projects that require data cleaning, data modelling and data visualisation
3. Strong coding ability in Python
4. Knowledge of version control systems e.g. GitHub
5. Ability to work collaboratively with people from a variety of technical and non-technical backgrounds
6. Track record in working proactively and independently (at home and in the office)
7. Committed to equality, diversity and inclusion, actively addressing areas of potential bias
1. Experience working with Microsoft Azure or deploying web apps through a cloud service
2. Experience working with non-relational databases
3. Experience with machine learning
4. Experience developing dashboards and automated processes
Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter.
This is an exciting time as the department has recently joined the newly formed School of Life Course and Population Sciences. This will bring together very considerable clinical, scientific, and population/global health strengths. There are already many examples of joint working and collaboration with our new School, and it is envisaged that there will be significant opportunities to collaborate further and draw upon the critical mass of clinical, methodological, and applied researchers in the new, integrated School. The School will be one of the largest in the Faculty with strong links to the NIHR BRC and NIHR Applied Research Collaboration and with King’s Health Partners Clinical Academic Groups and Institutes, with the enormous potential to further leverage these synergies.
About the Faculty: https://www.kcl.ac.uk/lsm/index.aspx