Prinesh Ramanuj
Information Analyst @Leicestershire Partnership NHS Trust
Signup · Get unlimited contacts
WORK HISTORY
Information Analyst @Leicestershire Partnership NHS Trust
Leicester, GB
Experienced in handling complex datasets and creating insightful data visualisations using Excel, Qlik Sense, Power BI, and Tableau to support data-driven decision-making at LPT. Skilled in developing interactive dashboards, reports, and analytical tools that enhance operational efficiency. Proficient in SQL and Visual Studio for extracting, manipulating, and analysing data, optimising queries, and integrating data systems. Adept in Python and R for advanced data analysis, statistical modelling, and visualisation. Utilises machine learning techniques and forecasting methods to analyse NHS data, identify trends, and predict future outcomes. Expertise in Visual Basic for automation, streamlining data processes, and improving reporting accuracy. Delivers daily, weekly, and monthly reports for NHS operations, tracking performance metrics and presenting actionable insights. Experienced in analysing quality and safety-related KPIs to support service improvement. Engages effectively with internal and external stakeholders, including clinicians and commissioners, to develop evidence-based models of care. Ensures GDPR compliance in handling sensitive workforce, patient, and organisational data. Skilled in communicating complex, sensitive information to diverse audiences while overcoming barriers to understanding. Proficient in designing and delivering formal presentations to senior stakeholders, clinicians, and external partners, translating complex data insights into clear, actionable strategies. Builds strong working relationships with clinical and non-clinical staff, using frontline insights to drive data-driven improvements in patient care and service models. Adaptable to new systems, including ESR, and quick to learn emerging technologies. Influences stakeholders to embrace data-driven improvements through negotiation and persuasion. A committed team player fostering collaboration, continuous improvement, and a culture of analytical excellence at LPT.
ABOUT PRINESH RAMANUJ
Detail-oriented and analytical Data Analyst with eight years’ experience in the NHS, specialising in extracting, analysing, and presenting complex healthcare data. Proficient in SQL, Python, R, and Visual Basic for data manipulation, as well as data visualization tools such as Power BI, Tableau, Qlik View and Qlik Sense. Skilled in forecasting, machine learning techniques, and performance metric analysis to support evidence-based decision-making. Adept at stakeholder engagement, communicating insights effectively to clinical and non-clinical teams, and driving data-driven improvements in service quality and efficiency. A strong team player who actively seeks feedback and learning opportunities to enhance analytical capabilities and service impact. I come from a self-learning background, which has fostered my ability to quickly acquire and apply new skills and technologies. Throughout my career, I have consistently demonstrated my capacity to learn efficiently, adapting to new tools, systems, and methodologies with ease. My commitment to continuous self-improvement has enabled me to stay ahead of technological advancements in the data analytics field. This ability to learn quickly and apply new knowledge effectively has been crucial in mastering tools such as SQL, Python, R, and Visual Basic, along with visualisation platforms like Power BI, Tableau, and Qlik Sense. I am adept at picking up new software and analytical techniques, which has allowed me to successfully integrate and apply these skills. Moreover, I believe this self-driven learning approach has enhanced my problem-solving skills, as I am able to independently explore and resolve challenges. It allows me to proactively seek out new methods and innovative solutions, making me an adaptable and resourceful asset to any team.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.