Analytics Specialist Data Science

This is an exciting opportunity to join The Christie’s Clinical Outcomes and Data Unit (CODU) as an Analytics Specialist with Data Science. Along with Analytics, Data Science and Statistics (ADSS) colleagues, you will provide dedicated support for the exciting new development of the Trust’s Joint Analytics for Cancer (JAC) data platform and Future Christie digital ambitions, working closely with data engineering colleagues, supporting data mapping, data cataloguing and data quality improvement, utilising NLP and machine learning methods to help deliver the JAC and Future Christie 5 year plan.

As a data expert, you will interpret information from multiple health care systems providing advice on best approaches for data utilisation and explaining technical data aspects to non‑data experts.

When completing your application please ensure you have read the attached job description and clearly evidence how you meet the essential and desirable criteria that are indicated as being assessed via the application form – short‑listing will be based on this evidence and you will also be asked about these should you be shortlisted for interview. After all applications have been reviewed, those applicants who have been shortlisted will be assessed via a two‑stage interview process.

First round of interviews will be virtual and involve a technical test.

The second round will be an in‑person interview held at our Withington site, a virtual option will not be offered for the second round.

Being the lead analyst assigned to support the JAC and Future Christie deliverables:

• Providing analytical insight and guidance to aid complex decision making.
• Working with DE colleagues on mapping, cataloguing and data quality evaluation and reporting.
• Investigating outliers and data quality issues.
• Generating data quality reports and advising on the implications of poor data quality.
• Providing data and analytical expertise to inform the procurement of the new JAC data platform.
• Designing and producing dashboards and statistical reports, incorporating data science tools and techniques where appropriate.
• Presenting findings and analytical products to a wide range of audiences (technical and non‑technical), including methodologies and recommendations where appropriate.
• Identifying the most applicable techniques and variables to meet the project’s needs, investigating conflicting information.
• Completing project documentation and delivering projects to agreed specifications.
• Working as part of the ADSS team of analytics specialists to manage data and statistical/data science requests; triaging, prioritising and delegating requests.
• Recommending and leading on delivering improvements in reporting, software or other systems, particularly where the improvements contribute to the performance of the system or accuracy of data.
• Being an expert in the Trust’s reporting requirements and supporting this function – identifying and leading on opportunities to improve efficiency and accuracy of reporting.
• Leading on key projects with data engineering to improve the data repository, escalating where changes may impact on analyst products.
• Testing own work and peer‑reviewing team member’s work.
• Prioritising and planning own work appropriately.
• Exploring and staying up to date with various analytics and data science techniques, advising on those optimal for the purpose and to improve own work area.
• Contacting customers and digital colleagues, dealing with issues associated with access to data – delivering bad news to customers and stakeholders when necessary, suggesting alternative approaches, providing support to reduce data quality issues, and acting as point of escalation.
• Using various software to provide data insight tools using appropriate analytical techniques – acting as an expert at understanding problems and utilising these tools.
• Maintaining exceptional attention to detail to help ensure high quality and efficient new processes are implemented to improve CODU functions.
• Working closely with other teams in digital services (software development, data engineering) to understand cross‑over work streams and potential implications.
• Being…