Job summary
This is a fantastic opportunity to demonstrate your technical expertise as a Divisional Data Analyst to within our Business Informatics team at ESNEFT.
You are responsible for supporting the Head of Analytics, Deputy Head of Analytics, and Surgical Specialties Analytical Lead in the seamless delivery of bespoke robust business intelligence to stakeholders across the Musculoskeletal (MSK) and Specialised Surgeries Division.
The role will have a core focus on the provision of bespoke analysis to operational and clinical customers by using analytical techniques including regular performance dashboards, demand and capacity modelling, statistical analysis, and responding to ad hoc queries for information and analysis.
You will be a visible presence within the Division, ensuring that operational and clinical colleagues in MSK and Specialised Surgeries have timely access to the insights they need to make strategical and tactical decisions.
You will possess excellent communication skills, with the ability to convey complex information in an easily understood way to non-analytical audiences. Additionally, you should have hands-on experience with benchmarking tools, activity forecasting, modelling, and statistical analysis.
You will have experience using analytical and programming tools/languages such as SQL, Power BI, and R. Moreover, your background should include working within a quality assurance framework and enabling report automation.
Main duties of the job
Consult/coordinate with relevant administrative and clinical stakeholders to plan and implement the collection and submission of mandatory datasets (national or local requirements). Develop and maintain performance management frameworks for the division ensuring reports remain up to date, relevant and accurate. Working with members of the BI team to ensure local reports and national returns are submitted according to relevant timetables. Provide timely performance analysis to inform key meetings. Specify, design, and implement new processes or systems to support developing information requirements. Complete statistical analysis of activity to ensure robust forecasting is available to stakeholders, in line with Trust timetables, with Divisional insight. To develop and maintain activity planning and forecasting software/ files/ database tables.
About us
We are ESNEFT and we provide hospital and community health services to almost one million people across east Suffolk and north Essex. Our dedicated staff deliver care from acute hospitals in Colchester and Ipswich, community hospitals, surgeries, community clinics and in patients' own homes.
We are the largest NHS organisation in East Anglia, employing more than 12,000 staff.
We pride ourselves on supporting our staff. We offer a wide range of training and development opportunities, as well as flexible working options.
Along with supporting you to achieve your career goals we offer a generous pension scheme, unsocial hours payments (where applicable), 27 days annual leave on commencement (pro rata) and access to a range of NHS discounts. Our Staff Health and Wellbeing programme offer a variety of services.
Our philosophy is thatTime Mattersto everyone. Across the Trust, we concentrate on improving the things we do and removing those which cause time delays for our staff and patients.
We are investing in our commitment to Time Matters with a partnership with leading electronic patient record (EPR) supplier Epic. This digital transformation will bring what's widely regarded as the world's best EPR system to ESNEFT, transforming life in hospital for staff and patients.
If you are passionate about patient care and want to develop your skills and knowledge, then we want to hear from you.
Find out about living and working here
Job description
Job responsibilities
Analytical Support
Provide specialist quantitative and qualitative complex data analysis to Operational Managers and Executive Managers to support the Business to maintain quality, safety and financial sustainability. Lead the development of analytical tools for operational and clinical colleagues in the Division. Sourcing, validating, analysing, interpreting, and presenting data for customers both internal and external to the Trust. Provide accurate analytical data to support the implementation of transformation and efficiency programmes, in conjunction with the Surgical Specialties Analytics Lead and the wider Analytics Team. Respond to complex queries requiring the utilisation of specialist knowledge across a range of areas, work procedures and practices, underpinned by theoretical knowledge and relevant practical experience. Follow a quality assurance framework to ensure the accuracy and robustness of your results. Consistently aim to enhance the efficiency of project outputs, such as through the automation of reports.
For full details of theresponsibilitiesand dutiesof this role please see the attached job description.
Person Specification
Qualifications
Essential
Relevant degree or equivalent qualification or significant experience of working at degree level in a quantitative subject ( Maths, Statistics, Physics, Economics, Operational Research). Evidence of continued professional development
Desirable
Python/R certification Microsoft Azure certifications Power BI certification Registered with AphA professionally or actively working towards registration
Experience
Essential
Proven experience of working in an analyst/management/leadership role. Experience of facilitating change in practice to improve services Project management/co-ordination Experience using SQL and managing databases Experience of working to a Quality Assurance Framework
Desirable
Experience using Python/R Experience using Microsoft Azure, including Data Bricks Experience developing Power BI reports Experience developing demand and capacity analysis Experience with report automation
Knowledge and Skills
Essential
Business planning/annual planning Use of IT systems (, Word, Excel, Outlook) - standard keyboard skills Good understanding of change management Advanced user of MS Office suite, in particular Excel, Access, and SQL Server Understanding of the NHS and current agenda Demonstrable knowledge of service improvements and project management Risk management and governance Quality assurance Working knowledge of NHS Data Standards and Information Systems. Benchmarking, modelling, and forecasting skills
Desirable
Demand and Capacity Planning techniques Statistical modelling tools (generalised linear models, hypothesis test) Advanced knowledge of supervised and unsupervised machine learning techniques In depth knowledge of performance returns, definitions, guidance, and performance management in the acute sector Understanding of NHS data flows and information issues, including Data Standards, the Secondary Uses Service and commissioning information Understanding of the Model Health System and associated metrics NHS IT systems